US20190300957A1

US20190300957A1 - Methods of diagnosing inflammatory bowel disease through rnaset2

Info

Publication number: US20190300957A1
Application number: US16/084,858
Authority: US
Inventors: Rebecca Gonsky; Stephan R. Targan; Richard L. DEEM; Philip Fleshner; Dermot P. McGovern; Janine Bilsborough
Original assignee: Cedars Sinai Medical Center
Current assignee: Cedars Sinai Medical Center
Priority date: 2016-03-17
Filing date: 2017-03-17
Publication date: 2019-10-03
Also published as: EP3430172A1; US20220162703A1; JP7082945B2; US11186872B2; KR102464372B1; KR20220011802A; JP2022095664A; WO2017161342A1; CN109462996A; KR20220153109A; JP2019509739A; KR20180127416A; EP3430172A4

Abstract

The present invention describes methods of diagnosing inflammatory bowel disease, including but not limited to Crohn's Disease (CD), Ulcerative Colitis (UC), and/or Medically Refractive Ulcerative Colitis (MR-UC), using RNA-SET2, TL1A and/or IFN-_Υ. The invention further provides a process for patient identification and/or stratification.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a U.S. National Phase of International Application No. PCT/US2017/023082 filed Mar. 17, 2017, which claims the benefit of U.S. Provisional Ser. Nos. 62/457,048 filed Feb. 9, 2017 and 62/309,817 filed Mar. 17, 2016, all of which are incorporated herein in their entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under Grant Nos. DK043211, DK046763, DK062413, HS021747, AI067068, DE023798, DK084554, RR033176 and TR000124 awarded by the National Institutes of Health. The government has certain rights in the invention.

FIELD OF INVENTION

The invention relates to inflammatory bowel disease and RNASET2 as a biomarker for disease severity and targeting anti-TL1A therapy.

BACKGROUND

All publications herein are incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. The following description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
Inflammatory bowel disease (IBD) has two common forms, Crohn's disease (CD) and ulcerative colitis (UC), which are chronic, relapsing inflammatory disorders of the gastrointestinal tract. Genetic factors play an important role in IBD pathogenesis, as evidenced by the increased rates of IBD in Ashkenazi Jews, familial aggregation of IBD, and increased concordance for IBD in monozygotic compared to dizygotic twin pairs (S. Vermeire, P. Rutgeerts, Genes Immun 6, 637 (2005)). Moreover, genetic analyses have linked IBD to specific genetic variants. CD and UC are thought to be related disorders that share some genetic susceptibility loci but differ at others.
IBD is generally believed to be triggered in genetically susceptible individuals by an inappropriate immune response to the commensal flora. The high clinical heterogeneity and genetic complexity of CD and UC suggest that the underlying biological pathways driving disease almost certainly differ in subgroups of patients. Thus, the development of early and targeted therapeutics requires subgroup stratification and prognostic biomarker identification, particularly in predicting an overall mild, compared to severe, disease course. Although 201 IBD susceptibility loci have been identified, little is known regarding their functional significance. Genetic variation in TNFSF15 is associated with CD in multiple populations, and the protein it encodes, TL1A, is a key mediator of mucosal inflammation. TL1A expression is up-regulated in inflamed regions of the intestine in both CD and UC. In IBD patients, elevated TL1A levels correlate with TNFSF15 genotype and disease severity. CD patients with elevated serum/tissue levels of TL1A have increased risk of developing fibrosis/stricturing disease behavior. In vitro, TL1A synergizes with interleukin 12 (IL-12) and interleukin 18 (IL-18) (12/18), leading to rapid enhancement of IFN-γ production, another key mediator of mucosal inflammation.
Therefore, there remains a need in the art for methods of diagnosing and identifying patients for treatment with IBD, CD, UC and/or MR-UC.

BRIEF DESCRIPTION OF THE FIGURES

Exemplary embodiments are illustrated in referenced figures. It is intended that the embodiments and figures disclosed herein are to be considered illustrative rather than restrictive.

FIG. 1 depicts RNASET2 eQTL microarray in uninvolved small intestine, in accordance with various embodiments of the invention.

FIG. 2 shows that the RNASET2 major allele is associated with decreased expression of RNASET2 in sigmoid colon and rectum of CD patients, in accordance with various embodiments of the invention.

FIG. 3 shows that the RNASET2 major allele is associated with decreased expression of RNASET2 in sigmoid colon and rectum of UC patients, in accordance with various embodiments of the invention.

FIG. 4 shows that the RNASET2 risk allele is associated with decreased expression of RNASET2 in inflamed large bowel in CD and UC patients, in accordance with various embodiments of the invention. Similar results were observed for rs1819333.

FIG. 5 shows that the RNASET2 major allele is associated with decreased RNASET2 expression in small bowel from CD surgeries, in accordance with various embodiments of the invention.

FIG. 6 depicts RNASET2 eQTL in EBV Transformed B Cell Lines, in accordance with various embodiments of the invention. The major allele is associated with lower levels of RNASET2 mRNA expression in EBV transformed B cell lines.

FIG. 7 depicts RNASET2 expression following IL-12, IL-18, and/or TL1A and treatment, in accordance with various embodiments of the invention.

FIGS. 8A-8C depict RNASET2 expression in CD patients, in accordance with various embodiments of the invention. A) RNASET2 expression in patients with none or 1 multiple disease flares per year. B) RNASET2 expression following TL1A treatment in patients who were medically refractive requiring surgical intervention for disease management or no surgery. C) RNASET2 expression based upon disease flares per year in 32 CD patients, encompassing additional data samples.

FIG. 9 shows a decreased expression of RNASET2 in IBD patients with RNASET2 risk alleles, in accordance with various embodiments of the invention.

FIG. 10 depicts RNASET2 methylation versus GWAS p values in CD and UC patients, in accordance with various embodiments of the invention.

FIG. 11 depicts the eQTL of RNASET2 in refractory IBD, in accordance with various embodiments of the invention. RNASET2 SNPs (rs2149085, rs1819333 and rs9355610) from CD3+ peripheral T cells from 11 CD and 10 UC patients requiring surgical intervention for disease management, using an Illumina expression array.

FIG. 12 depicts the eQTL of RNASET2 in CD small bowel (ileal) surgical resection of 85 CD patients using an Agilent expression array, in accordance with various embodiments of the invention.

FIGS. 13A-13D depict the mQTL of RNASET2 in refractory IBD, in accordance with various embodiments of the invention. A) mQTL of RNASET2 in refractory IBD and B) normal or mild disease patients. C) mQTL (cg25258033) of CD3+ peripheral T cells from 20 CD patients with refractory disease requiring surgical intervention for disease management and D) 16 patients who were responsive to IBD therapeutics and 9 normal controls, encompassing additional data samples.

FIGS. 14A-14B depict the mapping of eQTL and mQTL across RNASET2 in patients with refractory or mild disease, in accordance with various embodiments of the invention. A) eQTL and mQTL across RNASET2 in patients with refractory or mild disease. B) eQTL and mQTL calculated using CD3+ T cells from both the periphery and mucosal compartments from patients with refractory or mild disease (including normal patients), encompassing additional data samples.

FIG. 15 depicts sorting and IFNγ expression of CD4+ T cells stimulated with IL-12, IL-18 and/or TL1A, in accordance with various embodiments of the invention. Histograms of side scatter vs. IFN-γ for CD4+T cells stimulated with recombinant human IL-12 (500 pg/ml) and IL-18 (50 ng/ml) and TL1A (100 ng/ml) for 8 h from 4 donor (D1-4).

FIG. 16 depicts a dendrogram of hierarchical clustering using centered correlation and average linkage, in accordance with various embodiments of the invention.

FIG. 17 depicts a class prediction analysis classifying the IFNγ-secreting and non-secreting subgroups based on expression level, in accordance with various embodiments of the invention. Heatmap of 764 predictor genes.

FIG. 18 depicts a proportion of genes differentially expressed that was increased in GWAS versus other regions, in accordance with various embodiments of the invention.

FIG. 19 depicts 183 transcribed IBD associated SNP regions in the T cells, in accordance with various embodiments of the invention.

FIG. 20 depicts a volcano plot of the class predictor GWAS transcripts of IBD risk predictor genes, in accordance with various embodiments of the invention.

FIGS. 21A-21B show that silencing RNASET2 enhances IFN-γ secretion, in accordance with various embodiments of the invention. A) Inhibition of RNASET2 by RNASET2 siRNA. B) Effect of RNASET2 silencing on IFN-γ secretion. Enhanced IFN-γ expression in cellos transfected with RNASET2 siRNA compared to control scrambled siRNA.

FIG. 22 demonstrates the inverse correlation of IFN-γ and RNASET2 expression in accordance with various embodiments of the invention.

FIG. 23 demonstrates a negative correlation of RNASET2 methylation and expression in CD3⁺ T cells (cg25258033, located 1.4 kb within the first intron) in 21 IBD patients, in accordance with various embodiments of the invention.

FIGS. 24A-24D depict correlation of RNASET2 and TNFSF15 expression in CD3+ T cells from patients with refractory disease requiring surgical intervention for disease management, using RNA-seq, in accordance with various embodiments of the invention. A) Correlation of RNASET2 versus TL1A in refractory CD. B) Correlation of RNASET2 and TNFSF15 expression in CD3+ peripheral T cells from 38 CD patients, C) depicts data from 100 CD patients and D) depicts combined data from 138 patients.

FIG. 25 depicts the correlation expression of RNASET2 versus A) PU.1 and B) ELF1, in accordance with various embodiments of the invention. The risk SNP rs2149092 C/T (SEQ ID NO: 2) abolishes the IRF4, PU.1, and ELF-1 binding site. C—non-risk and T=risk allele.

FIG. 26 depicts correlation of expression and methylation located within 100 kb of the RNASET2 transcriptional start site in 21 IBD patients, in accordance with various embodiments of the invention.

FIG. 27 depicts IFN-γ expression of IFN-γ producing and non-producing levels in CD4+ T cells, in accordance with various embodiments of the invention.

FIG. 28 depicts the correlation of GWAS p values with eQTL p values over the RNASET2 locus, in accordance with various embodiments of the invention. GWAS p values are based upon data from 18729 CD and 34897 controls. eQTL p values are based upon genotyping and RNA-seq based expression of RNASET2 for 71 CD patients with refractory disease, requiring surgical intervention for disease management.

FIG. 29 depicts the effect of RNASET2 silencing on IFN-γ secretion, in accordance with various embodiments of the invention. Inhibition of RNASET2 expression by RNASET2-specific siRNA was greater than 50% in all experiments.

FIG. 30 depicts an association of decreased expression of RNASET2 with ASCA Sero-positivity, in accordance with various embodiments of the invention.

FIG. 31 depicts an association of a decreased expression of RNASET2 with penetrating disease, in accordance with various embodiments of the invention. Expression of RNASET2 by RNA-seq for 71 CD patients based upon Montreal disease classification (B1, B2, and B3).

FIG. 32 depicts that patients with RNASET2 disease associated SNPs exhibited a shorter time to reoperation, in accordance with various embodiments of the invention. Time between surgeries based upon carriage for IBD risk SNP rs9355610 (SEQ ID NO: 3) for 154 CD patients who underwent multiple surgeries.

FIG. 33 depicts that the rs2149092 SNP (SEQ ID NO: 2) Alters DNA Shape.

FIG. 34 depicts the correlation of RNASET2 versus Ets1 expression, in accordance with various embodiments of the invention.

FIG. 35 depicts that the rs2149092 SNP (SEQ ID NO: 2) distorts DNA shape at the Ets1 binding site.

FIGS. 36A-36C depict identification of potential regulatory function of RNASET2 disease associated variant rs2149092 (SEQ ID NO: 2) the prospective regulatory role of RNASET2 variant rs2149092 (C-non-risk allele/T-risk allele), in accordance with various embodiments of the invention. A) Predicted disruption of rs2149092 C to T variation in the binding motifs for ETS and IRF4 transcription factors. Central ETS in the variant motif is underlined. B) CHIP-seq and histone modification profiles for ETS1, IRF4 and SPI1 transcription factor binding and histone H3K4me1 and H3K4ac aligned with the genomic sequence surrounding rs2149092 variant. C) Correlation of expression of RNASET2 and multiple ETS and JUN transcription factors in CD3+ peripheral T cells from 108 CD patients requiring surgical intervention for disease management, using RNA-seq.

FIGS. 37A-37G depict the effect of RNASET2 silencing on IFN-γ secretion and cellular aggregation, in accordance with various embodiments of the invention. A) Silencing of RNASET2 expression by RNASET2 or control (NC) siRNA. B) Effect of RNASET2 silencing on IFN-γ secretion. Panels A and B are representative of 6 out of 7 experiments (FIG. 29) with similar results. C) CD4+ T cells were either not treated (UT) or D) stimulated with TL1A for 24 hours. Intracellular IFN-γ staining and cellular aggregations were measured by flow cytometry. Cells were gated on IFN-γ secreting and non-secreting populations (left panels) and then using propidium iodide (PI) analyzed for single and aggregate cell fractions (histograms, right panels). The first peak in each histogram corresponds to single cells (black bracket) and the remaining peaks to cellular aggregates (gray bracket). Representative of 4 experiments. E) Proportion of single cells and cellular aggregates in IFN-γ secreting (IFN-γ+) and non-secreting (IFN-γ−) populations following TL1A stimulation. F) Fold increase in number of IFN-γ secreting cells (Average of 4 experiments). G) CD4+ T cells were pretreated with control IgG or LFA1 blocking Ab (aLFA1) prior to TL1A stimulation. Overall p value for LFA1 mediated blocking of IFN-γ secretion, measured by ELISA, was 0.047.

FIG. 38 depicts in accordance with various embodiments of the invention, the association of RNASET2 disease risk variant SNPs at the time of surgery with therapeutic failure of thiopurine or anti-TNF therapy, ANCA sero-positivity and an increased length of intestinal resection (data summarized in Table 18).

FIG. 39 depicts in accordance with various embodiments of the invention, the association of RNASET2 disease risk variant SNPs with disease recurrence in 38 patients who were not receiving postoperative prophylaxis. Post-operative endoscopies were performed and classified by Rutgeerts score. (data summarized in Table 18).

FIG. 40 depicts tissue-specific functional annotation of RNASET2 locus. Heatmap of H3K4me3, H3K4me1 and RNAseq data from REMC.

FIG. 41 depicts the correlation of RNASET2 expression and multiple ETS and IRF4 transcription factors in CD3+peripheral T cells from 108 CD patients with refractory disease, using RNA-seq.

FIG. 42 depicts in accordance with various embodiments of the invention, a heat-map illustrating protein expression of indicated genes in CD4+T cells relative to untreated cells following silencing with control (NC) or RNASET2 siRNA. Results are from 4 healthy donors. The right column depicts differential gene expression in IFN-γ secreting compared to non-secreting CD4+T cells.

FIG. 43 depicts in accordance with various embodiments of the invention, clinical disease parameters associated with level of ICAM1 expression (measured by RNA-seq) for 71 CD patients based upon IgG ASCA sero-positivity (left panel) or pre-op therapeutic failure of anti-TNF (middle panel) or thiopurine (right panel).

DESCRIPTION OF THE INVENTION

All references cited herein are incorporated by reference in their entirety as though fully set forth. The sequences related to RNASET2 are also incorporated by reference in their entirety as though fully set forth via the rs number disclosed. Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Singleton et al., Dictionary of Microbiology and Molecular Biology 3^rd ed., Revised, J. Wiley & Sons (New York, N.Y. 2006); and Sambrook et al., Molecular Cloning: A Laboratory Manual 4^th ed., Cold Spring Harbor Laboratory Press (Cold Spring Harbor, N.Y. 2012), provide one skilled in the art with a general guide to many of the terms used in the present application. For references on how to prepare antibodies, see D. Lane, Antibodies: A Laboratory Manual 2^nd ed. (Cold Spring Harbor Press, Cold Spring Harbor N.Y., 2013); Kohler and Milstein, (1976) Eur. J. Immunol. 6: 511; Queen et al. U.S. Pat. No. 5,585,089; Riechmann et al., Nature 332: 323 (1988); Bird, Science 242:423-42 (1988); Tomlinson I. and Holliger P. (2000) Methods Enzymol, 326, 461-479; Holliger P. (2005) Nat. Biotechnol. September; 23(9):1126-36).
One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention. Indeed, the present invention is in no way limited to the methods and materials described. For purposes of the present invention, the following terms are defined below.
Non-limiting examples of “Biological sample” as used herein means any biological material from which nucleic acids and/or proteins can be obtained. As non-limiting examples, the term encompasses whole blood, peripheral blood, plasma, serum, saliva, mucus, urine, semen, lymph, fecal extract, cheek swab, cells or other bodily fluid or tissue, including but not limited to tissue obtained through surgical biopsy or surgical resection. Alternatively, a sample can be obtained through primary patient derived cell lines, or archived patient samples in the form of preserved samples, or fresh frozen samples.
“Treatment” and “treating” as used herein refer to both therapeutic treatment and prophylactic or preventative measures, wherein the object is to prevent or slow down (lessen) the targeted pathologic condition, prevent the pathologic condition, pursue or obtain good overall survival, or lower the chances of the individual developing the condition even if the treatment is ultimately unsuccessful. Those in need of treatment include those already with the condition as well as those prone to have the condition or those in whom the condition is to be prevented.
“SNP” as used herein means single nucleotide polymorphism.
“Risk variant” as used herein refers to an allele, whose presence is associated with an increase in susceptibility to an inflammatory bowel disease, including but not limited to Crohn's Disease, Ulcerative Colitis and Medically Refractory-Ulcerative Colitis, relative to an individual who does not have the risk variant.
“IBD”, “CD”, “UC” and “MR-UC” as used herein refer to Inflammatory Bowel Disease, Crohn's Disease, Ulcerative Colitis and Medically Refractive Ulcerative Colitis, respectively.
As used herein, “IBD” includes “CD”, “UC” and/or “MR-UC”.
As used herein, “ANCA” means anti-neutrophil cytoplasmic antibodies.
As used herein, “OmpC” means outer membrane protein C.
As used herein, “eQTL” means expression quantitative trait loci.
As used herein, “mQTL” means methylation quantitative trait loci.
Non-limiting examples of RNASET2 SNPs are rs1819333, rs2149092, rs9355610, rs2149085, rs1410295 and rs9366093.
Described herein are methods of diagnosing inflammatory bowel disease using RNASET2, TL1A and/or IFN-γ as a biomarker of disease severity in a patient population and selecting the patient population for anti-TL1A therapy. Further described are methods of treating these patient populations.
RNASET2 (ribonuclease T2) encodes an extracellular RNase and is the only member of the human Rh/T2/S family of acid ribonucleases (acid hydrolyses), which are only active in acidic pH. The optimal activity of RNASET2 is at pH 5 and it has a preferential cleavage of poly-A and poly-U. It contains two regions with catalytic function and demonstrates a cleavage preference near adenylic acid followed by guanylic acid. Three isoforms have been detected for RNASET2, the 27KD, 31KD and 36KD isoforms. The 27KD and 31KD isoforms are thought to result from proteolytic cleavage of the 36KD isoform. All three isoforms are glycosylated. Subcellular fractionation reveals that full length RNASET2 is located in the endoplasmic reticulum and the two smaller RNASET2 proteolytic products are located in the lysosome fraction. RNASET2 is highly conserved among the phyla, from viruses to humans, suggesting an important evolutionary function.
TL1A (TNFSF15) is a tumor necrosis factor family member expressed primarily on activated cells of the immune system, such as monocytes, macrophages, and dendritic cells, following stimulation by immune complexes or through interaction with enteric microorganisms. TL1A expression is enhanced in inflammatory bowel disease and higher TL1A levels are associated with disease severity. Genome-Wide Association Studies (GWAS) have identified TNFSF15 SNPs to be associated with IBD. Studies have shown that neutralizing TL1A antibodies attenuate colitis in murine colitis models, while constitutive TL1A expression depicts a worsened murine ileo-cecal inflammation and intestinal fibrostenosis.
IFN-γ plays a key role in the generation and perpetuation of mucosal inflammation in IBD. TL1A augments IL-12/IL-18-mediated IFN-γ secretion in PB T cells.
The inventors identify RNASET2, an IBD susceptibility gene, as a component of TL1A-mediated enhancement of IFN-γ production. Moreover, functional variants of RNASET2 are associated with a more ‘severe’ CD phenotype characterized by one or more disease flares and stricturing/penetrating disease behavior. Without being bound to any particular theory, the inventor believes that RNASET2 serves as a therapeutic biomarker associated with severe disease pathobiology and allows for the identification of a patient population most likely to benefit from therapy targeted to the TL1A-driven inflammatory pathway. The TNFSF15 disease-associated variants are correlated with increased and sustained expression of TL1A. TNFSF15 has been identified and confirmed in GWAS as an IBD-associated gene and is believed to play a role in modulating the location and severity of intestinal inflammation, as well as development of stricturing disease. Transgenic mice with constitutive expression of TL1A developed intestinal inflammation along with ileal and colonic fibrosis, which was reversed by anti-TL1A treatment. In UC, there is a strong association between development of a medically refractory disease and the TL1A locus. Although TL1A is an important pro-inflammatory cytokine associated with IBD pathogenesis, the molecular pathways underlying enhanced cytokine secretion and inflammation were poorly understood. Described herein, the inventors investigated the TL1A-dependent molecular triggers that induce cytokine expression, particularly IFN-γ, in T cells. This approach identified down-modulation of RNASET2 as a component of TL1A-mediated enhancement of IFN-γ production.
The inventors demonstrate a functional association of RNASET2 disease risk SNPs with decreased expression and hyper-methylation in T cells isolated from CD patients, as well as, an association with clinical parameters suggestive of complicated/resistant disease behavior and rapid recurrence of disease. The inventors show the regulatory potential for ETS TF in modulating RNASET2 expression and the involvement of homotypic T cell aggregation via ICAM1 as a component of RNASET2 mediated up-regulation of IFN-γ production. The data distinguish RNASET2 as a potential therapeutic biomarker and identify unique pathways for additional therapeutic modulation within a defined IBD population.
The inventors found that, in IBD patients, there was a significant inverse correlation between the expression of RNASET2 and TNFSF15. In addition, the inventors demonstrate a functional association between DNA hyper-methylation and decreased expression of RNASET2.
The inventors found that there was significant eQTL overlap with RNASET2 IBD risk alleles identified through GWAS in samples isolated from the peripheral T cells and small bowel surgical resections. Significant RNASET2 eQTL (rs429083) has been described in a recent report that measured autoimmune associated risk variants in whole thymic tissue samples. This SNP demonstrated the most significant eQTL in the data, as well. Moreover, the study provides clinically relevant evidence that decreased expression levels of RNASET2 were correlated in CD patients with clinical parameters suggestive of complicated and resistant disease. Notably, CD patients carrying the RNASET2 disease risk SNPs displayed an increase in development of stricturing/penetrating disease behavior. RNASET2 expression was significantly lower in T cells isolated from CD patients exhibiting one or more disease flares per year. Similarly, RNASET2 expression is decreased in small bowel mucosal samples, as well as, in peripheral samples from medically refractory CD patients (9 out of 11 which were non-responsive to anti-TNF therapy), requiring surgical intervention for disease management. Consistent with the finding, a recent study reported significant RNASET2 eQTL in whole blood from patients resistant to anti-TNF therapy. Moreover, RNASET2 disease-associated SNPs correlated with therapeutic failure of anti-TNF therapy, and intestinal resection of >40 cm clinical characteristic of overall disease severity. In patients with a history of multiple resections, RNASET2 disease risk SNP was associated with a faster time to reoperation. Likewise, RNASET2 disease associated SNPs were associated in patients with endoscopic recurrence characterized by a more severe (>2) Rutgeerts score, which without being bound to any particular theory, can be predictive for early clinical recurrence and need for reoperation.
The transcriptional regulatory regions and binding factors modulating RNASET2 expression are likewise poorly defined. The majority of disease associated variants identified by GWAS reside within regulatory non-coding regions corresponding to promoters or enhancer sequences. Without being bound to any particular theory, studies suggest that alteration in transcriptional regulation via disruption of transcription factor binding sites may play a role in the disease process. In the present study the inventors utilized TF motif analysis to prioritize and identify from the large number of variants demonstrating eQTL and mQTL a prospective regulatory SNP. The rs2149092 disease associated SNP alters the conserved ETS consensus binding sequence and likely disrupts binding of multiple overlapping TF binding sites including IRF4, SPI1 and ELF1. Moreover, there is a strong positive correlation between the levels of RNASET2 expression and ETS and JUN TF family members. Interestingly, IRF4, SPI1 and ELF1 have been implicated in T cell development and IRF4 and ELF1 have been associated by GWAS with IBD. Without being bound to any particular theory, these data support a functional role for rs2049092 as a modulator of TF-DNA interactions and set the stage for future studies to determine the mechanistic pathways by which TL1A attenuates expression of RNASET2 in disease.
In the present study the inventors describe a functional relationship between RNASET2 and the cell adhesion molecule, ICAM1. Enhanced IFN-γ secretion in response to TL1A was accompanied by a decrease in RNASET2 expression on the one hand and an increase in ICAM1 levels on the other. TL1A mediated IFN-γ secretion was inhibited by Ab blockade of the ICAM1-LFA1 interaction. Although ICAM1-LFA1 engagement is classically defined as occurring between endothelial and T cells, these interactions have more recently been shown to play a critical role in mediating homotypic cellular aggregation of activated T cells. Homotypic T-T aggregates have been shown to promote synaptic-based cytokine delivery of IFN-γ and IL2 from one T cell to another, resulting in IL-2 receptor ligation and subsequent STATS phosphorylation. The inventors demonstrate that enhanced cellular aggregation is a hallmark of IFN-γ producing cells and TL1A-stimulation increases the number and size of the cellular aggregates. Without being bound to any particular theory, these findings suggest that RNASET2 may act through the integrin signaling pathway to modulate downstream IFN-γ secretion.
In conclusion, the inventors identified a novel functional and biological relationship between two IBD susceptibility genes, TNFSF15 and RNASET2. The inventors provide evidence that decreased RNASET2 expression is functionally implicated in both the TL1A driven pro-inflammatory cytokine production by activated T cells and functionally associated with the RNASET2 IBD susceptibility variants. Likewise, the present study demonstrates an association between decreased RNASET2 expression and a more severe form of IBD inflammation, which without wishing to be bound by any particular theory, we believe underlie disease pathology triggered by TL1A mediated pathways. Decreased expression and altered epigenetic DNA methylation of RNASET2 characterize a subset of IBD patients with a more severe disease phenotype. The inventors demonstrate a functional association of RNASET2 disease risk SNPs with decreased expression and hyper-methylation in T cells isolated from CD patients, as well as, an association with clinical parameters suggestive of complicated/resistant disease behavior and rapid recurrence of disease. The inventors show the regulatory potential for ETS TF in modulating RNASET2 expression and the involvement of homotypic T cell aggregation via ICAM1 as a component of RNASET2 mediated upregulation of IFN-γ production. The data distinguish RNASET2 as a potential therapeutic biomarker and identify unique pathways for additional therapeutic modulation within a defined IBD population. Thus, RNASET2 expression serves as a novel disease biomarker of a more severe form of inflammation identifying a patient population not responsive to current treatment strategies, whom may benefit from alternate RNASET2 mediated therapeutic approaches.
As disclosed herein, the inventors have identified RNASET2 associated SNPs in an IBD patient cohort. The inventors have identified RNASET2 associated SNPs in a CD patient cohort. The inventors have identified RNASET2 associated SNPs in a UC patient cohort. The inventors have identified RNASET2 associated SNPs in a MR-UC patient cohort. The SNPs were associated with disease location, disease behavior and need for surgery. The inventors have further identified RNASET2 as a biomarker for disease severity and associated RNASET2 risk SNPs in an IBD patient cohort. RNASET2 has been identified as a biomarker for disease severity and associated RNASET2 risk SNPs in a CD patient cohort. RNASET2 has been identified as a biomarker for disease severity and associated RNASET2 risk SNPs in a UC patient cohort. RNASET2 has been identified as a biomarker for disease severity and associated RNASET2 risk SNPs in a MR-UC patient cohort. In addition, the inventors demonstrate a correlation between RNASET2, TL1A expression and IFN-γ secretion.
The present invention is based, at least in part, on these findings. The present invention addresses the need in the art for methods of diagnosing patients with IBD and identifying patients in need of treatment, using RNASET2, TL1A and/or IFN-γ. The invention further provides a process for patient identification and/or stratification.

Diagnosis

Various embodiments of the present invention provide for a method of diagnosing inflammatory bowel disease (IBD) in a subject, comprising: obtaining a sample from the subject; subjecting the sample to an assay adapted to determine the presence or absence of one or more risk variants at the RNASET2 gene; and diagnosing IBD in the subject based on the presence of one or more risk variants at the RNASET2 gene. In some embodiments, inflammatory bowel disease is Crohn's disease, ulcerative colitis or medically refractive ulcerative colitis. In various embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610, rs2149085, rs1410295 or rs9366093. In various embodiments, the subject is diagnosed with IBD if 2, 3, 4, 5 or 6 RNASET2 risk variants as described herein are present. In various embodiments, the risk allele for rs2149085 is the T allele. In various other embodiments, the RNASET2 risk variants are the RNASET2 risk variant rs429083 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the RNASET2 risk variants is one or more of the RNASET2 risk variants in Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, and 13 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610 or rs2149085. In various embodiments, the subject is diagnosed with IBD if 2, 3, or 4, RNASET2 risk variants rs1819333, rs2149092, rs9355610 or rs2149085, as described herein are present. In other embodiments, the presence of a greater number of risk variants in the sample indicates that the subject is in greater need of treatment. In some embodiments, the detection of RNASET2 risk variants is indicative of the need for treatment in the subject. In yet other embodiments, the subject is identified as needing anti-TL1A therapy. In various embodiments, the subject diagnosed with IBD demonstrates therapeutic failure of thiopurine and anti-TNF therapy. In various other embodiments, the subject diagnosed with IBD is determined to need surgical intervention. In some embodiments, the surgical intervention is intestinal resection.

TABLE 1

RNASET2 risk variants

	SNP	SEQ ID NO:

	rs1819333	1
	rs2149092	2
	rs9355610	3
	rs2149085	4
	rs1410295	5
	rs9366093	6

In other embodiments, the method of diagnosing inflammatory bowel disease (IBD) in a subject described herein comprises determining the expression level of RNASET2, TL1A and/or IFN-γ. In some embodiments, a subject with decreased RNASET2, and/or increased TL1A and/or IFN-γ levels is diagnosed with IBD. In various embodiments, inflammatory bowel disease is Crohn's disease. In various embodiments, inflammatory bowel disease is ulcerative colitis. In various embodiments, inflammatory bowel disease is medically refractive ulcerative colitis. In various embodiments, inflammatory bowel disease is a CD patient who required surgical intervention for disease management. In yet other embodiments, a subject with decreased RNASET2, and/or increased TL1A and/or IFN-γ levels is identified as a subject in need of a treatment that increases RNASET2, and/or decreases TL1A and/or IFN-γ. In other embodiments, the subject is identified as needing anti-TL1A therapy. In yet other embodiments, the subject is identified as needing a treatment that causes an increase in RNASET2. In certain other embodiments, the subject is identified as needing a treatment that causes a decrease in IFN-γ and/or TL1A.
In various embodiments, the detection of RNASET2 risk variants and/or RNASET2, TL1A and/or IFN-γ expression levels can be accomplished by analyzing nucleic acids of a biological sample from the subject. A variety of apparatuses and/or methods, including, without limitation, polymerase chain reaction based analysis, sequence analysis and electrophoretic analysis can be used to detect RNASET2 risk variants. The expression levels of RNASET2, TL1A and/or IFN-γ can be detected using a variety of apparatuses and/or methods, including, without limitation, quantitative PCR, northern blot and microarrays. As used herein, the term “nucleic acid” means a polynucleotide such as a single or double-stranded DNA or RNA molecule including, for example, genomic DNA, cDNA and mRNA. The term nucleic acid encompasses nucleic acid molecules of both natural and synthetic origin as well as molecules of linear, circular or branched configuration representing either the sense or antisense strand, or both, of a native nucleic acid molecule.
In various other embodiments, determining the expression level of RNASET2, TL1A and/or IFN-γ can be accomplished by analyzing the proteins of a biological sample from the subject. A variety of apparatuses and/or methods, including, without limitation, ELISA, immunohistochemistry, and western blot can be used to detect RNASET2, TL1A and/or IFN-γ expression levels.
Various embodiments of the present invention also provide for a method of diagnosing medically refractive ulcerative colitis (MR-UC), comprising: obtaining a sample from the subject; subjecting the sample to an assay adapted to determine the presence or absence of one or more risk variants at the RNASET2; and diagnosing MR-UC in the subject based on the presence of one or more risk variants at the RNASET2 gene. In various embodiments, the one or more risk variants at the RNASET2 gene are rs1819333, rs2149092, rs9355610, rs2149085, rs1410295 or rs9366093. In various embodiments, the risk allele for rs2149085 is the T allele. In various other embodiments, the RNASET2 risk variants are the RNASET2 risk variant rs429083 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the RNASET2 risk variants is one or more of the RNASET2 risk variants in Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, and 13 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610 or rs2149085. In various embodiments, the subject is diagnosed with IBD if 2, 3, or 4, RNASET2 risk variants rs1819333, rs2149092, rs9355610 or rs2149085 as described herein are present.
In various embodiments, the subject diagnosed with MR-UC demonstrates therapeutic failure of thiopurine and anti-TNF therapy. In various other embodiments, the subject diagnosed with MR-UC is determined to need surgical intervention. In some embodiments, the surgical intervention is intestinal resection. In various embodiments, the subject diagnosed with MR-UC is determined to need RNASET2 mediated therapy, such as but not limited to recombinant RNASET2 and anti-ICAM1. In various embodiments, the RNASET2 mediated therapy is an antibody or small molecule that targets genes that are upstream and/or downstream of RNASET2.
In various other embodiments, the methods further comprise determining the level of methylation of RNASET2, and diagnosing IBD in a subject who has an increase in RNASET2 methylation. In other embodiments, the level of RNASET2 methylation is determined to diagnose a subject with MR-UC. In some embodiments, the subject is identified as needing a treatment that causes a decrease in RNASET2 methylation. In other embodiments, the subject is identified as needing an anti-TL1A therapy.
Various embodiments of the present invention provide for the treatment of subjects diagnosed with MR-UC. MR-UC subjects are refractory to current conventional medical therapy used, such as anti-TNF therapy, thiopurine therapy, corticosteroids and cyclosporine. In various embodiments, the subjects diagnosed with MR-UC are treated with non-conventional treatments, such as, but not limited to treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In various embodiments, the subject diagnosed with MR-UC is determined to need RNASET2 mediated therapy, such as but not limited to recombinant RNASET2 and anti-ICAM1. In various embodiments, the RNASET2 mediated therapy is an antibody or small molecule that targets genes that are upstream and/or downstream of RNASET2.
In various embodiments, the subject is identified as needing a treatment that mimics, RNASET2, TL1A and/or IFN-γ. In other embodiments, the subject is identified as needing a treatment that modulates RNASET2, TL1A and/or IFN-γ. In some other embodiments, the subject is identified as needing a treatment that targets RNASET2, TL1A and/or IFN-γ. In yet other embodiments, the subject is identified as needing a treatment that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In various embodiments, the disease is IBD. In various embodiments, the disease is CD. In various embodiments, the disease is UC. In various embodiments, the disease is MR-UC. In various embodiments, the subject diagnosed is a CD patients who required surgical intervention for disease management.
In various embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with decreased expression of RNASET2. In other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with decreased expression of RNASET2 in peripheral and mucosal tissues. In some other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with DNA hypermethylation in patients requiring surgical intervention for disease management. In yet other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with therapeutic failure of thiopurine and/or anti-TNF therapy. In some other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with ANCA sero-positivity. In various other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with increased overall length of intestinal resection.
Subject Identification and/or Stratification
Various embodiments of the present invention provide for a process of identifying a subject with inflammatory bowel disease for treatment, comprising: determining the expression level of RNASET2, TL1A and/or IFN-γ; and identifying the subject in need of treatment as a subject with decreased RNASET2, and/or increased TL1A and/or IFN-γ levels. In various embodiments, the inflammatory bowel disease is Crohn's disease. In various embodiments, the inflammatory bowel disease is ulcerative colitis. In various embodiments, the inflammatory bowel disease is medically refractive ulcerative colitis. In various other embodiments, the subject is identified as needing a treatment that causes an increase in RNASET2. In yet other embodiments, the subject is identified as needing a treatment that causes a decrease in TL1A and/or IFN-γ. In certain embodiments, the subject is identified as needing anti-TL1A therapy. In some embodiments, the subject is identified as needing a treatment that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides.
“Patient Risk Stratification” as used herein means the process of separating subjects into risk groups in need of treatment.
Various embodiments of the present invention provide for a process of patient risk stratification to identify a subject in need of treatment, relative to a healthy individual. In various embodiments, the subject is stratified based on the detection of RNASET2, TL1A and/or IFN-γ in a biological sample from the subject. In some embodiments, a decrease in RNASET2 is indicative of a patient having IBD, in need of treatment. In some embodiments, a decrease in RNASET2 is indicative of a patient having CD, in need of treatment. In some embodiments, the patient is a CD patient who requires surgical intervention for disease management. In some embodiments, a decrease in RNASET2 is indicative of a patient having UC, in need of treatment. In some embodiments, a decrease in RNASET2 is indicative of a patient having MR-UC in need of treatment. In various other embodiments, an increase in TL1A and/or IFN-γ is indicative of a patient having IBD, in need of treatment. In various other embodiments, an increase in TL1A and/or IFN-γ is indicative of a patient having CD, in need of treatment. In various other embodiments, an increase in TL1A and/or IFN-γ is indicative of a patient having UC, in need of treatment. In various other embodiments, an increase in TL1A and/or IFN-γ is indicative of a patient having MR-UC, in need of treatment. In certain other embodiments, a decrease in RNASET2, an increase in TL1A, and an increase in IFN-γ is indicative of a subject having IBD, in need of treatment. In certain other embodiments, a decrease in RNASET2, an increase in TL1A, and an increase in IFN-γ is indicative of a subject having CD, in need of treatment. In certain other embodiments, a decrease in RNASET2, an increase in TL1A, and an increase in IFN-γ is indicative of a subject having UC, in need of treatment. In certain other embodiments, a decrease in RNASET2, an increase in TL1A, and an increase in IFN-γ is indicative of a subject having MR-UC, in need of treatment. In various embodiments, detection of the genes provides a guide for the treatment of the subject. In certain embodiments, the subject is identified as needing a treatment that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In various other embodiments, the process of patient risk stratification to identify a subject in need of treatment is relative to a healthy individual who has been previously treated. In various other embodiments, the process of patient risk stratification to identify a subject in need of treatment is relative to a medically responsive individual.
Various embodiments of the present invention provide for the treatment of subjects diagnosed with MR-UC. MR-UC subjects are refractory to current conventional medical therapy used, such as anti-TNF therapy, thiopurine therapy, corticosteroids and cyclosporine. In various embodiments, the subjects diagnosed with MR-UC are treated with non-conventional treatments, such as, but not limited to treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In various embodiments, the subject diagnosed with MR-UC is determined to need RNASET2 mediated therapy, such as but not limited to recombinant RNASET2 and anti-ICAM1. In various embodiments, the RNASET2 mediated therapy is an antibody or small molecule that targets genes that are upstream and/or downstream of RNASET2.
In other embodiments, the process for subject identification and/or stratification described herein comprises determining the presence of one or more risk variants. In certain embodiments, the one or more risk variants comprise rs1819333, rs2149092, rs9355610, rs2149085, rs1410295 or rs9366093. In various embodiments, the process comprises identifying the subject with IBD in need of treatment if 2, 3, 4, 5 or 6 RNASET2 risk variants as described herein are present. In various embodiments, the risk allele for rs2149085 is the T allele. In various other embodiments, the RNASET2 risk variants are the RNASET2 risk variant rs429083 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the RNASET2 risk variants is one or more of the RNASET2 risk variants in Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, and 13 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610 or rs2149085. In various embodiments, the subject is diagnosed with IBD if 2, 3, or 4, RNASET2 risk variants rs1819333, rs2149092, rs9355610 or rs2149085 as described herein are present. In various other embodiments, the detection of the risk variants in the biological sample stratifies the subject into a group needing treatment. In other embodiments, the presence of a greater number of risk variants in the sample indicates that the subject is in greater need of treatment. In some embodiments, the detection of RNASET2 risk variants is indicative of the need for treatment in the subject. In some embodiments, the subject is identified as needing anti-TL1A therapy. In various embodiments, the subject identified as needing RNASET2 mediated therapy, such as but not limited to recombinant RNASET2 and anti-ICAM1. In various embodiments, the RNASET2 mediated therapy is an antibody or small molecule that targets genes that are upstream and/or downstream of RNASET2.
In various embodiments, the detection of RNASET2 risk variants can be accomplished by analyzing nucleic acids of a biological sample from the subject, as discussed herein.
In other embodiments, the process for subject identification and/or stratification described herein further comprises assaying the sample to detect the level of RNASET2 methylation, relative to a healthy individual. In some embodiments, a subject with an increased level of RNASET2 methylation is identified as a subject in need of treatment. In some embodiments, the sample is assessed for the level of RNASET2 methylation and one or more RNASET2 risk variants. In certain embodiments, a subject who has an increase in RNASET2 methylation and the presence of one or more RNASET2 risk variants is identified as a subject in need of treatment. In other embodiments, the sample is assessed for the level of RNASET2 methylation and the expression levels of RNASET2, TL1A and/or IFN-γ. In certain embodiments, a subject who has an increase in RNASET2 methylation and a decrease in RNASET2, an increase in TL1A and/or IFN-γ is identified as a subject in need of treatment. In certain embodiments, the subject is identified as needing a treatment that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In some embodiments, the subject is identified as needing anti-TL1A therapy. In some embodiments, the subject is identified as needing a treatment that causes a decrease in RNASET2 methylation. In various other embodiments, the detection of an increase in RNASET2 methylation is indicative of a patient with severe CD requiring surgery. In a further embodiment, the subject is identified as needing a treatment that comprises colectomy and/or anti-TL1A therapy.
In various other embodiments, the process for subject identification and/or stratification described herein can further comprise assaying the sample to detect an increase or decrease of at least one microbial antigen (serological factor), relative to a healthy individual. In some embodiments, the microbial antigens (serological factors) assessed comprise ANCA, ASCA, OmpC, I2 and CBir. In some embodiments, the sample is assessed for one or more microbial antigens (serological factors) and one or more RNASET2 risk variants. In certain embodiments, a subject who has one or more risk serological factors and the presence of one or more RNASET2 risk variants is identified as a subject in need of treatment. In yet other embodiments, the sample is assessed for one or more risk serological factors and the expression levels of RNASET2, TL1A and/or IFN-γ. In certain embodiments, a subject who has one or more risk serological factors and a decrease in RNASET2, an increase in TL1A and/or IFN-γ is identified as a subject in need of treatment. In some embodiments, the subject is identified as needing a treatment that mimics, modulates and/or targets RNASET2, TL1A and/or IFNγ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In other embodiments, the treatment is anti-TL1A therapy. In various embodiments, the treatment is an RNASET2 mediated therapy, such as but not limited to recombinant RNASET2 and anti-ICAM1. In various embodiments, the RNASET2 mediated therapy is an antibody or small molecule that targets genes that are upstream and/or downstream of RNASET2.
In various embodiments the subject identified with IBD demonstrates therapeutic failure of thiopurine and anti-TNF therapy. In various other embodiments, the subject identified with IBD is determined to need surgical intervention. In some other embodiments, the surgical intervention is intestinal resection. Various embodiments of the present invention also provide for a method of selecting surgery for a subject having Inflammatory Bowel Disease, comprising: obtaining a sample from the subject; subjecting the sample to an assay adapted to determine the presence or absence of one or more risk variants at the RNASET2 gene; diagnosing MR-UC in the subject based on the presence of one or more risk variants at the RNASET2 gene; and selecting surgery for the subject diagnosed with MR-UC. In some embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610, rs2149085, rs1410295 or rs9366093. In various other embodiments, the RNASET2 risk variants are the RNASET2 risk variant rs429083 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the RNASET2 risk variants is one or more of the RNASET2 risk variants in Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, and 13 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610 or rs2149085. In various embodiments, the subject is diagnosed with IBD if 2, 3, or 4, RNASET2 risk variants rs1819333, rs2149092, rs9355610 or rs2149085 as described herein are present. In some embodiments, the method further comprises determining the level of methylation of RNASET2. In various embodiments, a subject with an increased level of RNASET2 methylation is identified as a subject in need of surgery. In other embodiments, the subject with an increase in RNASET2 methylation and the presence of one or more risk variants at the RNASET2 gene is identified as a subject in need of surgery.
In various embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with decreased expression of RNASET2. In other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with decreased expression of RNASET2 in peripheral and mucosal tissues. In some other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with DNA hypermethylation in patients requiring surgical intervention for disease management. In yet other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with therapeutic failure of thiopurine and/or anti-TNF therapy. In some other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with ANCA sero-positivity. In various other embodiments, the presence of one or more risk variants at the RNASET2 gene is associated with increased overall length of intestinal resection.
Various embodiments of the present invention provide for a method of selecting a therapy for a subject having Inflammatory Bowel Disease, comprising: obtaining a sample from the subject; subjecting the sample to an assay adapted to determine the presence or absence of one or more risk variants at the RNASET2 gene; diagnosing medically refractive ulcerative colitis (MR-UC) in the subject based on the presence of one or more risk variants at the RNASET2 gene; and selecting surgery as the therapy and not selecting thiopurine or anti-TNF as the therapy for the subject diagnosed with MR-UC. In various embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610, rs2149085, rs1410295 or rs9366093. In various other embodiments, the RNASET2 risk variants are the RNASET2 risk variant rs429083 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the RNASET2 risk variants is one or more of the RNASET2 risk variants in Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, and 13 and an RNASET2 risk variant selected from the group consisting of rs1819333, rs2149092, rs9355610, rs2149085, rs1410295, rs9366093, and combinations thereof. In various other embodiments, the one or more risk variants at the RNASET2 gene is rs1819333, rs2149092, rs9355610 or rs2149085. In various embodiments, the subject is diagnosed with IBD if 2, 3, or 4, RNASET2 risk variants rs1819333, rs2149092, rs9355610 or rs2149085 as described herein are present. In yet other embodiments, the method further comprises determining the level of methylation of RNASET2, wherein increased methylation is indicative of a subject requiring surgical intervention.
Various embodiments of the present invention provide for the treatment of subjects diagnosed with MR-UC. MR-UC subjects are refractory to current conventional medical therapy used, such as anti-TNF therapy, thiopurine therapy, corticosteroids and cyclosporine. In various embodiments, the subjects diagnosed with MR-UC are treated with non-conventional treatments, such as, but not limited to treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In various embodiments, the subject diagnosed with MR-UC is determined to need RNASET2 mediated therapy, such as but not limited to recombinant RNASET2 and anti-ICAM1. In various embodiments, the RNASET2 mediated therapy is an antibody or small molecule that targets genes that are upstream and/or downstream of RNASET2.

Detection of Methylation

Various embodiments provide for a method of diagnosing a subject with inflammatory bowel disease (IBD). In some embodiments, the method comprises determining the level of methylation of RNASET2; and identifying the subject with IBD as a subject with increased RNASET2 methylation. In other embodiments, the method comprises identifying the subject with IBD as a subject who has increased RNASET2 methylation and who has the presence of one or more risk variants at the RNASET2 gene. In various other embodiments, the method comprises determining the expression level of RNASET2, TL1A and/or IFN-γ; and diagnosing the subject with IBD if the subject has a decrease in RNASET2, an increase in TL1A, an increase in IFN-γ and/or an increase in RNASET2 methylation.
Various embodiments provide for a process of identifying a subject with inflammatory bowel disease (IBD) in need of treatment. In some embodiments, the method comprises determining the level of methylation of RNASET2; and identifying the subject in need of treatment as a subject with increased RNASET2 methylation. In other embodiments, the expression level of RNASET2, TL1A and/or IFN-γ and the level of methylation of RNASET2 are determined, to identify a subject with inflammatory bowel disease in need of treatment. In various embodiments, the method comprises determining a subject in need of treatment as a subject who has a decrease in RNASET2, an increase in TL1A, an increase in IFN-γ, and/or an increase in RNASET2 methylation. In various other embodiments, the method comprises determining the presence or absence of one or more risk variants at the RNASET2 gene and identifying a subject with IBD in need of treatment as a subject who has an increase in RNASET2 methylation and the presence of one or more RNASET2 risk variants.
In various embodiments, an increase in methylation is indicative of a subject requiring surgical intervention. In yet other embodiments, an increase in RNASET2 methylation is indicative of requiring surgical intervention.
Various methods to detect levels of methylation include, but are not limited to the following assays, mass spectrometry, methylation-specific PCR (MSP), whole genome bisulfite sequencing, (BS-Seq), the HELP assay, ChIP-on-chip assays, restriction landmark genomic scanning, methylated DNA immunoprecipitation (MeDIP, MeDIP-chip, MeDIPseq), pyrosequencing of bisulfite treated DNA, molecular break light assay for DNA adenine methyltransferase activity, methyl sensitive southern blotting, separate native DNA into methylated and unmethylated fractions using MethylCpG Binding Proteins (MBPs) and/or Methyl Binding Domain (MBD), MethylationEPIC BeadChip, Illumina Infinium Methylation 450 BeadChip, High Resolution Melt Analysis (HRM or HRMA), and/or ancient DNA methylation reconstruction.
Various embodiments of the invention provide for the treatment of a subject diagnosed with inflammatory bowel disease (IBD) by the method comprising obtaining a sample from the subject; subjecting the sample to an assay adapted to determine the presence or absence of one or more risk variants at the RNASET2 gene; and diagnosing IBD in the subject based on the presence of one or more risk variants at the RNASET2 gene. In various embodiments, inflammatory bowel disease is Crohn's disease, ulcerative colitis or medically refractive ulcerative colitis.
Various embodiments of the invention provide for the treatment of a subject diagnosed with medically refractive ulcerative colitis (MR-UC) by the method comprising, obtaining a sample from the subject; subjecting the sample to an assay adapted to determine the presence or absence of one or more risk variants at the RNASET2; and diagnosing MR-UC in the subject based on the presence of one or more risk variants at the RNASET2 gene.
Various embodiments of the present invention provide for the treatment of subjects diagnosed with MR-UC. MR-UC subjects are refractory to current conventional medical therapy used, such as anti-TNF therapy and thiopurine therapy. In various embodiments, the subjects diagnosed with MR-UC are treated with non-conventional treatments, such as, but not limited to treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ. In various embodiments, treatments that mimics, modulates and/or targets RNASET2, TL1A and/or IFN-γ can comprise antibodies and or silencing oligonucleotides. In various embodiments, the subject diagnosed with MR-UC is determined to need RNASET2 mediated therapy, such as but not limited to recombinant RNASET2 and anti-ICAM1. In various embodiments, the RNASET2 mediated therapy is an antibody or small molecule that targets genes that are upstream and/or downstream of RNASET2.

Biological Samples, Sample Preparation and Gene Expression Detection

In various embodiments, the steps involved in the current invention comprise obtaining a biological sample from a subject. The biological sample may be obtained either through surgical biopsy or surgical resection. Alternatively, a sample can be obtained through primary patient derived cell lines, or archived patient samples in the form of FFPE (Formalin fixed, paraffin embedded) samples, or fresh frozen samples. A sample may also comprise whole blood, peripheral blood, plasma, serum, saliva, cheek swab, or other bodily fluid or tissue. In various embodiments, the sample comprises tissue from the large and/or small intestine. In various other embodiments, the large intestine sample comprises the cecum, colon (the ascending colon, the transverse colon, the descending colon, and the sigmoid colon), rectum and/or the anal canal. In yet other embodiments, the small intestine sample comprises the duodenum, jejunum, and/or the ileum.
Nucleic acid or protein samples derived from the biological sample (i.e., tissue and/or cells) of a subject that can be used in the methods of the invention can be prepared by means well known in the art. For example, surgical procedures or needle biopsy aspiration can be used to collect the biological samples from a subject. In some embodiments, it is important to enrich and/or purify the abnormal tissue and/or cell samples from the normal tissue and/or cell samples. In other embodiments, the abnormal tissue and/or cell samples can then be microdissected to reduce the amount of normal tissue contamination prior to extraction of genomic nucleic acid or pre-RNA for use in the methods of the invention. Such enrichment and/or purification can be accomplished according to methods well-known in the art, such as needle microdissection, laser microdissection, fluorescence activated cell sorting, and immunological cell sorting.
Analysis of the nucleic acid and/or protein from an individual may be performed using any of various techniques. In various embodiments, assaying gene expression levels for RNASET2 comprises northern blot, reverse transcription PCR, real-time PCR, serial analysis of gene expression (SAGE), DNA microarray, tiling array, RNA-Seq, or a combination thereof. In various other embodiments, the gene expression levels for RNASET2, TL1A and/or IFN-γ are assayed. In other embodiments, the level of RNASET2 methylation is determined.
In various embodiments, methods and systems to detect protein expression include but are not limited to ELISA, immunohistochemistry, western blot, flow cytometry, fluorescence in situ hybridization (FISH), radioimmuno assays, and affinity purification.
The analysis of gene expression levels may involve amplification of an individual's nucleic acid by the polymerase chain reaction. Use of the polymerase chain reaction for the amplification of nucleic acids is well known in the art (see, for example, Mullis et al. (Eds.), The Polymerase Chain Reaction, Birkhauser, Boston, (1994)).
Methods of “quantitative” amplification are well known to those of skill in the art. For example, quantitative PCR involves simultaneously co-amplifying a known quantity of a control sequence using the same primers. This provides an internal standard that may be used to calibrate the PCR reaction. Detailed protocols for quantitative PCR are provided in Innis, et al. (1990) PCR Protocols, A Guide to Methods and Applications, Academic Press, Inc. N.Y.). Measurement of DNA copy number at microsatellite loci using quantitative PCR analysis is described in Ginzonger, et al. (2000) Cancer Research 60:5405-5409. The known nucleic acid sequence for the genes is sufficient to enable one of skill in the art to routinely select primers to amplify any portion of the gene. Fluorogenic quantitative PCR may also be used in the methods of the invention. In fluorogenic quantitative PCR, quantitation is based on amount of fluorescence signals, e.g., TaqMan and sybr green.
Other suitable amplification methods include, but are not limited to, ligase chain reaction (LCR) (see Wu and Wallace (1989) Genomics 4: 560, Landegren, et al. (1988) Science 241:1077, and Barringer et al. (1990) Gene 89: 117), transcription amplification (Kwoh, et al. (1989) Proc. Natl. Acad. Sci. USA 86: 1173), self-sustained sequence replication (Guatelli, et al. (1990) Proc. Nat. Acad. Sci. USA 87: 1874), dot PCR, and linker adapter PCR, etc.
A DNA sample suitable for hybridization can be obtained, e.g., by polymerase chain reaction (PCR) amplification of genomic DNA, fragments of genomic DNA, fragments of genomic DNA ligated to adaptor sequences or cloned sequences. Computer programs that are well known in the art can be used in the design of primers with the desired specificity and optimal amplification properties, such as Oligo version 5.0 (National Biosciences). PCR methods are well known in the art, and are described, for example, in Innis et al., eds., 1990, PCR Protocols: A Guide to Methods And Applications, Academic Press Inc., San Diego, Calif. It will be apparent to one skilled in the art that controlled robotic systems are useful for isolating and amplifying nucleic acids and can be used.

Hybridization

The nucleic acid samples derived from a subject used in the methods of the invention can be hybridized to arrays comprising probes (e.g., oligonucleotide probes) in order to identify RNASET2, TL1A and/or IFN-γ and in instances wherein a housekeeping gene expression is also to be assessed, comprising probes in order to identify selected housekeeping genes. In particular embodiments, the probes used in the methods of the invention comprise an array of probes that can be tiled on a DNA chip (e.g., SNP oligonucleotide probes). Hybridization and wash conditions used in the methods of the invention are chosen so that the nucleic acid samples to be analyzed by the invention specifically bind or specifically hybridize to the complementary oligonucleotide sequences of the array, preferably to a specific array site, wherein its complementary DNA is located. In some embodiments, the complementary DNA can be completely matched or mismatched to some degree as used, for example, in Affymetrix oligonucleotide arrays. The single-stranded synthetic oligodeoxyribonucleic acid DNA probes of an array may need to be denatured prior to contact with the nucleic acid samples from a subject, e.g., to remove hairpins or dimers which form due to self-complementary sequences.
Optimal hybridization conditions will depend on the length of the probes and type of nucleic acid samples from a subject. General parameters for specific (i.e., stringent) hybridization conditions for nucleic acids are described in Sambrook and Russel, Molecular Cloning: A Laboratory Manual 4^th ed., Cold Spring Harbor Laboratory Press (Cold Spring Harbor, N.Y. 2012); Ausubel et al., eds., 1989, Current Protocols in Molecules Biology, Vol. 1, Green Publishing Associates, Inc., John Wiley & Sons, Inc., New York, at pp. 2.10.1-2.10.16. Exemplary useful hybridization conditions are provided in, e.g., Tijessen, 1993, Hybridization with Nucleic Acid Probes, Elsevier Science Publishers B. V. and Kricka, 1992, Nonisotopic DNA Probe Techniques, Academic Press, San Diego, Calif.

Oligonucleotide Nucleic Acid Arrays

In some embodiments of the methods of the present invention, DNA arrays can be used to determine the expression levels of genes, by measuring the level of hybridization of the nucleic acid sequence to oligonucleotide probes that comprise complementary sequences. Various formats of DNA arrays that employ oligonucleotide “probes,” (i.e., nucleic acid molecules having defined sequences) are well known to those of skill in the art. Typically, a set of nucleic acid probes, each of which has a defined sequence, is immobilized on a solid support in such a manner that each different probe is immobilized to a predetermined region. In certain embodiments, the set of probes forms an array of positionally-addressable binding (e.g., hybridization) sites on a support. Each of such binding sites comprises a plurality of oligonucleotide molecules of a probe bound to the predetermined region on the support. More specifically, each probe of the array is preferably located at a known, predetermined position on the solid support such that the identity (i.e., the sequence) of each probe can be determined from its position on the array (i.e., on the support or surface). Microarrays can be made in a number of ways, of which several are described herein. However produced, microarrays share certain characteristics, they are reproducible, allowing multiple copies of a given array to be produced and easily compared with each other.
In some embodiments, the microarrays are made from materials that are stable under binding (e.g., nucleic acid hybridization) conditions. The microarrays are preferably small, e.g., between about 1 cm²and 25 cm², preferably about 1 to 3 cm². However, both larger and smaller arrays are also contemplated and may be preferable, e.g., for simultaneously evaluating a very large number of different probes. Oligonucleotide probes can be synthesized directly on a support to form the array. The probes can be attached to a solid support or surface, which may be made, e.g., from glass, plastic (e.g., polypropylene, nylon), polyacrylamide, nitrocellulose, gel, or other porous or nonporous material. The set of immobilized probes or the array of immobilized probes is contacted with a sample containing labeled nucleic acid species so that nucleic acids having sequences complementary to an immobilized probe hybridize or bind to the probe. After separation of, e.g., by washing off, any unbound material, the bound, labeled sequences are detected and measured. The measurement is typically conducted with computer assistance. DNA array technologies have made it possible to determine the expression level of RNASET2, TL1A and/or IFN-γ, housekeeping genes and the methylation state of RNASET2.
In certain embodiments, high-density oligonucleotide arrays are used in the methods of the invention. These arrays containing thousands of oligonucleotides complementary to defined sequences, at defined locations on a surface can be synthesized in situ on the surface by, for example, photolithographic techniques (see, e.g., Fodor et al., 1991, Science 251:767-773; Pease et al., 1994, Proc. Natl. Acad. Sci. U.S.A. 91:5022-5026; Lockhart et al., 1996, Nature Biotechnology 14:1675; U.S. Pat. Nos. 5,578,832; 5,556,752; 5,510,270; 5,445,934; 5,744,305; and 6,040,138). Methods for generating arrays using inkjet technology for in situ oligonucleotide synthesis are also known in the art (see, e.g., Blanchard, International Patent Publication WO 98/41531, published Sep. 24, 1998; Blanchard et al., 1996, Biosensors And Bioelectronics 11:687-690; Blanchard, 1998, in Synthetic DNA Arrays in Genetic Engineering, Vol. 20, J. K. Setlow, Ed., Plenum Press, New York at pages 111-123). Another method for attaching the nucleic acids to a surface is by printing on glass plates, as is described generally by Schena et al. (1995, Science 270:467-470). Other methods for making microarrays, e.g., by masking (Maskos and Southern, 1992, Nucl. Acids. Res. 20:1679-1684), may also be used. When these methods are used, oligonucleotides (e.g., 15 to 60-mers) of known sequence are synthesized directly on a surface such as a derivatized glass slide. The array produced can be redundant, with several oligonucleotide molecules corresponding to each informative locus of interest (e.g., SNPs, RFLPs, STRs, etc.).
One exemplary means for generating the oligonucleotide probes of the DNA array is by synthesis of synthetic polynucleotides or oligonucleotides, e.g., using N-phosphonate or phosphoramidite chemistries (Froehler et al., 1986, Nucleic Acid Res. 14:5399-5407; McBride et al., 1983, Tetrahedron Lett. 24:246-248). Synthetic sequences are typically between about 15 and about 600 bases in length, more typically between about 20 and about 100 bases, most preferably between about 40 and about 70 bases in length. In some embodiments, synthetic nucleic acids include non-natural bases, such as, but by no means limited to, inosine. As noted above, nucleic acid analogues may be used as binding sites for hybridization. An example of a suitable nucleic acid analogue is peptide nucleic acid (see, e.g., Egholm et al., 1993, Nature 363:566-568; U.S. Pat. No. 5,539,083). In alternative embodiments, the hybridization sites (i.e., the probes) are made from plasmid or phage clones of regions of genomic DNA corresponding to SNPs or the complement thereof. The size of the oligonucleotide probes used in the methods of the invention can be at least 10, 20, 25, 30, 35, 40, 45, or 50 nucleotides in length. It is well known in the art that although hybridization is selective for complementary sequences, other sequences which are not perfectly complementary may also hybridize to a given probe at some level. Thus, multiple oligonucleotide probes with slight variations can be used, to optimize hybridization of samples. To further optimize hybridization, hybridization stringency condition, e.g., the hybridization temperature and the salt concentrations, may be altered by methods that are well known in the art.
In various embodiments, the high-density oligonucleotide arrays used in the methods of the invention comprise oligonucleotides corresponding to RNASET2, TL1A and/or IFN-γ and housekeeping genes. In other embodiments, the oligonucleotides correspond to methylated RNASET2. The oligonucleotide probes may comprise DNA or DNA “mimics” (e.g., derivatives and analogues) corresponding to a portion of each informative locus of interest (e.g., SNPs, RFLPs, STRs, etc.) in a subject's genome. The oligonucleotide probes can be modified at the base moiety, at the sugar moiety, or at the phosphate backbone. Exemplary DNA mimics include, e.g., phosphorothioates. For each SNP locus, a plurality of different oligonucleotides may be used that are complementary to the sequences of sample nucleic acids. For example, for a single informative locus of interest (e.g., SNPs, RFLPs, STRs, etc.) about 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, or more different oligonucleotides can be used. Each of the oligonucleotides for a particular informative locus of interest may have a slight variation in perfect matches, mismatches, and flanking sequence around the SNP. In certain embodiments, the probes are generated such that the probes for a particular informative locus of interest comprise overlapping and/or successive overlapping sequences which span or are tiled across a genomic region containing the target site, where all the probes contain the target site. By way of example, overlapping probe sequences can be tiled at steps of a predetermined base interval, e. g. at steps of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 bases intervals. In certain embodiments, the assays can be performed using arrays suitable for use with molecular inversion probe protocols such as described by Wang et al. (2007) Genome Biol. 8, R246. For oligonucleotide probes targeted at nucleic acid species of closely resembled (i.e., homologous) sequences, “cross-hybridization” among similar probes can significantly contaminate and confuse the results of hybridization measurements. Cross-hybridization is a particularly significant concern in the detection of SNPs since the sequence to be detected (i.e., the particular SNP) must be distinguished from other sequences that differ by only a single nucleotide. Cross-hybridization can be minimized by regulating either the hybridization stringency condition and/or during post-hybridization washings. Highly stringent conditions allow detection of allelic variants of a nucleotide sequence, e.g., about 1 mismatch per 10-30 nucleotides. There is no single hybridization or washing condition which is optimal for all different nucleic acid sequences, these conditions can be identical to those suggested by the manufacturer or can be adjusted by one of skill in the art. In some embodiments, the probes used in the methods of the invention are immobilized (i.e., tiled) on a glass slide called a chip. For example, a DNA microarray can comprises a chip on which oligonucleotides (purified single-stranded DNA sequences in solution) have been robotically printed in an (approximately) rectangular array with each spot on the array corresponds to a single DNA sample which encodes an oligonucleotide. In summary the process comprises, flooding the DNA microarray chip with a labeled sample under conditions suitable for hybridization to occur between the slide sequences and the labeled sample, then the array is washed and dried, and the array is scanned with a laser microscope to detect hybridization. In certain embodiments there are at least 250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000, 17,000, 18,000, 19,000, 20,000, 21,000, 22,000, 23,000, 24,000, 25,000, 26,000, 27,000, 28,000, 29,000, 30,000, 31,000, 32,000, 33,000, 34,000, 35,000, 36,000, 37,000, 38,000, 39,000, 40,000, 41,000, 42,000, 43,000, 44,000, 45,000, 50,000, 60,000, 70,000, 80,000, 90,000, 100,000 or more or any range in between, of RNASET2, TL1A and/or IFN-γ or housekeeping genes for which probes appear on the array (with match/mismatch probes for a single locus of interest or probes tiled across a single locus of interest counting as one locus of interest). The maximum number of RNASET2, TL1A and/or IFN-γ or housekeeping genes being probed per array is determined by the size of the genome and genetic diversity of the subjects species. DNA chips are well known in the art and can be purchased in pre-5 fabricated form with sequences specific to particular species. In other embodiments, SNPs and/or DNA copy number can be detected and quantitated using sequencing methods, such as “next-generation sequencing methods” as described further above.

Labeling

In some embodiments, the protein, polypeptide, nucleic acid, fragments thereof, or fragments thereof ligated to adaptor regions used in the methods of the invention are detectably labeled. For example, the detectable label can be a fluorescent label, e.g., by incorporation of nucleotide analogues. Other labels suitable for use in the present invention include, but are not limited to, biotin, iminobiotin, antigens, cofactors, dinitrophenol, lipoic acid, olefinic compounds, detectable polypeptides, electron rich molecules, enzymes capable of generating a detectable signal by action upon a substrate, and radioactive isotopes.
Radioactive isotopes include that can be used in conjunction with the methods of the invention, but are not limited to, 32P and 14C. Fluorescent molecules suitable for the present invention include, but are not limited to, fluorescein and its derivatives, rhodamine and its derivatives, texas red, 5′carboxy-fluorescein (“FAM”), 2′, 7′-dimethoxy-4′, 5′-dichloro-6-carboxy-fluorescein (“JOE”), N, N, N′, N′-tetramethyl-6-carboxy-rhodamine (“TAMRA”), 6-carboxy-X-rhodamine (“ROX”), HEX, TET, IRD40, and IRD41.
Fluorescent molecules which are suitable for use according to the invention further include: cyamine dyes, including but not limited to Cy2, Cy3, Cy3.5, CY5, Cy5.5, Cy7 and FLUORX; BODIPY dyes including but not limited to BODIPY-FL, BODIPY-TR, BODIPY-TMR, BODIPY-630/650, and BODIPY-650/670; and ALEXA dyes, including but not limited to ALEXA-488, ALEXA-532, ALEXA-546, ALEXA-568, and ALEXA-594; as well as other fluorescent dyes which will be known to those who are skilled in the art. Electron rich indicator molecules suitable for the present invention include, but are not limited to, ferritin, hemocyanin and colloidal gold.
Two-color fluorescence labeling and detection schemes may also be used (Shena et al., 1995, Science 270:467-470). Use of two or more labels can be useful in detecting variations due to minor differences in experimental conditions (e.g., hybridization conditions). In some embodiments of the invention, at least 5, 10, 20, or 100 dyes of different colors can be used for labeling. Such labeling would also permit analysis of multiple samples simultaneously which is encompassed by the invention.
The labeled nucleic acid samples, fragments thereof, or fragments thereof ligated to adaptor regions that can be used in the methods of the invention are contacted to a plurality of oligonucleotide probes under conditions that allow sample nucleic acids having sequences complementary to the probes to hybridize thereto. Depending on the type of label used, the hybridization signals can be detected using methods well known to those of skill in the art including, but not limited to, X-Ray film, phosphor imager, or CCD camera. When fluorescently labeled probes are used, the fluorescence emissions at each site of a transcript array can be, preferably, detected by scanning confocal laser microscopy. In one embodiment, a separate scan, using the appropriate excitation line, is carried out for each of the two fluorophores used. Alternatively, a laser can be used that allows simultaneous specimen illumination at wavelengths specific to the two fluorophores and emissions from the two fluorophores can be analyzed simultaneously (see Shalon et al. (1996) Genome Res. 6, 639-645). In a preferred embodiment, the arrays are scanned with a laser fluorescence scanner with a computer controlled X-Y stage and a microscope objective. Sequential excitation of the two fluorophores is achieved with a multi-line, mixed gas laser, and the emitted light is split by wavelength and detected with two photomultiplier tubes. Such fluorescence laser scanning devices are described, e.g., in Schena et al. (1996) Genome Res. 6, 639-645. Alternatively, a fiber-optic bundle can be used such as that described by Ferguson et al. (1996) Nat. Biotech. 14, 1681-1684. The resulting signals can then be analyzed to determine the expression of RNASET2, TL1A and/or IFN-γ and housekeeping genes, using computer software.
In other embodiments, where genomic DNA of a subject is fragmented using restriction endonucleases and amplified prior to analysis, the amplification can comprise cloning regions of genomic DNA of the subject. In such methods, amplification of the DNA regions is achieved through the cloning process. For example, expression vectors can be engineered to express large quantities of particular fragments of genomic DNA of the subject (Sambrook and Russel, Molecular Cloning: A Laboratory Manual 4^th ed., Cold Spring Harbor Laboratory Press (Cold Spring Harbor, N.Y. 2012)).
In yet other embodiments, where the DNA of a subject is fragmented using restriction endonucleases and amplified prior to analysis, the amplification comprises expressing a nucleic acid encoding a gene, or a gene and flanking genomic regions of nucleic acids, from the subject. RNA (pre-messenger RNA) that comprises the entire transcript including introns is then isolated and used in the methods of the invention to analyze and provide a genetic signature of a cancer. In certain embodiments, no amplification is required. In such embodiments, the genomic DNA, or pre-RNA, of a subject may be fragmented using restriction endonucleases or other methods. The resulting fragments may be hybridized to SNP probes. Typically, greater quantities of DNA are needed to be isolated in comparison to the quantity of DNA or pre-mRNA needed where fragments are amplified. For example, where the nucleic acid of a subject is not amplified, a DNA sample of a subject for use in hybridization may be about 400 ng, 500 ng, 600 ng, 700 ng, 800 ng, 900 ng, or 1000 ng of DNA or greater. Alternatively, in other embodiments, methods are used that require very small amounts of nucleic acids for analysis, such as less than 400 ng, 300 ng, 200 ng, 100 ng, 90 ng, 85 ng, 80 ng, 75 ng, 70 ng, 65 ng, 60 ng, 55 ng, 50 ng, or less, such as is used for molecular inversion probe (MIP) assays. These techniques are particularly useful for analyzing clinical samples, such as paraffin embedded formalin-fixed material or small core needle biopsies, characterized as being readily available but generally having reduced DNA quality (e.g., small, fragmented DNA) and/or not providing large amounts of nucleic acids.
Once the expression levels have been determined, the resulting data can be analyzed using various algorithms, based on well-known methods used by those skilled in the art.

Kits

The present invention is also directed to a kit to diagnose a subject with IBD
and/or identifying a subject in need of treatment. The kit is useful for practicing the inventive method of diagnosing a subject and/or identifying a subject in need of treatment. The kit is an assemblage of materials or components, including at least one of the inventive compositions. Thus, in some embodiments the kit contains a composition including primers and probes for RNASET2, TL1A and/or IFN-γ, as described above.
The exact nature of the components configured in the inventive kit depends on its intended purpose. For example, some embodiments are configured for the purpose of assessing risk variants and/or gene expression levels. In some embodiments, the kit is configured to detect the gene expression levels of RNASET2 in a sample. In yet other embodiments, the kit is configured to detect the gene expression levels of RNASET2 and/or TL1A in a sample. In some other embodiments, the kit is configured to detect the gene expression levels of RNASET2, TL1A and/or IFN-γ in a sample. In various other embodiments, the kit is configured to detect RNASET2 risk variants in a sample. In yet other embodiments, the kit is configured to detect the level of RNASET2 methylation in a sample. In one embodiment, the kit is configured particularly for the purpose of assessing mammalian subjects. In another embodiment, the kit is configured particularly for the purpose of assessing human subjects. In further embodiments, the kit is configured for veterinary applications, assessing subjects such as, but not limited to, farm animals, domestic animals, and laboratory animals.
Instructions for use may be included in the kit. “Instructions for use” typically include a tangible expression describing the technique to be employed in using the components of the kit to effect a desired outcome, such as to diagnose a subject with IBD and/or identify a subject with IBD in need of treatment. Optionally, the kit also contains other useful components, such as, primers, diluents, buffers, pipetting or measuring tools or other useful paraphernalia as will be readily recognized by those of skill in the art.
The materials or components assembled in the kit can be provided to the practitioner stored in any convenient and suitable ways that preserve their operability and utility. For example the components can be in dissolved, dehydrated, or lyophilized form; they can be provided at room, refrigerated or frozen temperatures. The components are typically contained in suitable packaging material(s). As employed herein, the phrase “packaging material” refers to one or more physical structures used to house the contents of the kit, such as inventive compositions and the like. The packaging material is constructed by well-known methods, preferably to provide a sterile, contaminant-free environment. The packaging materials employed in the kit are those customarily utilized in gene expression assays. As used herein, the term “package” refers to a suitable solid matrix or material such as glass, plastic, paper, foil, and the like, capable of holding the individual kit components. Thus, for example, a package can be a glass vial used to contain suitable quantities of an inventive composition containing primers and probes for RNASET2, TL1A, IFN-γ and/or RNASET2 methylation. The packaging material generally has an external label which indicates the contents and/or purpose of the kit and/or its components.

EXAMPLES

The following examples are provided to better illustrate the claimed invention and are not to be interpreted as limiting the scope of the invention. To the extent that specific materials are mentioned, it is merely for purposes of illustration and is not intended to limit the invention. One skilled in the art may develop equivalent means or reactants without the exercise of inventive capacity and without departing from the scope of the invention.

Example 1

Loss of RNASET2 in zebrafish results in accumulation of undigested rRNA within lysosomes. The major allele of RNASET2 (i) is a risk for IBD, CD (rs9355610), B1 and both ANCA levels and pos/neg (rs1410925) and (ii) protective for B3 and both ASCA IgA and IgG levels and pos/neg (rs1410925) (Table 2). The major allele rs9355610 is associated with lower levels of RNASET2 mRNA expression in CD small intestine and rectum, EBV transformed B cells and CD3+ PBL from IBD patients. The major allele is also associated with RNASET2 mRNA in CD sigmoid colon. Low levels of RNASET2 and increased levels of pANCA are associated with the major allele. Methylation at the RNASET2 locus is inversely correlated with RNASET2 mRNA expression.

TABLE 2

Non-Jewish Qualitative and Quantitative Trait Association Data

				A1-
	iCHip	CH	BP	minor	Test	NMISS	OR	STAT	*P

rs9355610	CD
	6	167383075	A	ADD	3859	0.754	−4.041	5.33E−05	minor
	IBD
	6	167383075	A	ADD	4172	0.8591	−2.607	9.12E−03	allele
										protective

				Al-
	Trait	CH	BP	minor	Test	NMISS	OR	STAT	P

rs1410295	B1
	6	167345503	C	ADD	538	0.7168	−2.588	9.64E−03	minor
	ANCA
	6	167345503	C	ADD	875	0.7365	−2.626	8.65E−03	allele
										protective
	B3
	6	167345503	C	ADD	537	1.408	2.337	1.95E−02	minor
	ASCA
	6	167345503	C	ADD	820	1.379	2.926	3.44E−03	allele
	IgG									risk
	ASCA
	6	167345503	C	ADD	820	1.216	1.843	6.53E−02
	Panel

							BETA
							levels

rs1410295	ANCA	6	167345503	C	ADD	872	−4.608	−3.137	1.77E−03	minor
										allele
										protective
	ASCA
	6	167345503	C	ADD	820	4.024	2.363	1.84E−02	minor
	IgA									allele
	ASCA
	6	167345503	C	ADD	820	5.745	2.821	4.90E−03	risk
	IgG

All Non-Jewish

A1

A2

Non-Jewish CD

A1

A2

CHR	SNP	Minor	Major	MAF	CHR	SNP	Minor	Major	MAF

6	rs1410295	C	G	0.3541	6	rs1410295	C	G	0.3484
6	rs9355610	A	G	0.3305	6	rs9355610	A	G	0.2915

*Bonferroni p-value 1.7E−04

TABLE 3

RNASET2 Major allele is a risk for IBD and CD in a non-Jewish cohort

Pheno

SNP

CH

A1

A2

NMISS

OR

P

Type

OR

P

type

OR

P

type

rs9355610

6

A

G

5913

0.8218

4.50E−05

IBD

0.756

1.22E−06

CD

0.94

0.3695

UC

rs1819333

6

C

A

5813

0.8523

3.91E−04

IBD

0.782

4.04E−06

CD

0.988

0.8575

UC

*

SNP	CH	A1	A2	MAF	NCHROBS

rs1819333	6	C	A	0.4894	21278
rs9355610	6	A	G	0.3608	21278

A1 = minor allele;
A2 = major allele

TABLE 4

Qualitative Trait Associations in non-Jewish CD. Major allele is risk for colonic
disease in non-Jewish CD.

CD-										A1
Phenotype	CHR	SNP	BP	A1	A2	NMISS	OR	STAT	p	Freq

B1

	6	rs62436418	167265792	G	A	592	0.6992	−2.853	4.33E−03	0.3787
B2	6	rs62436418	167265792	G	A	592	1.395	−2.648	8.09E−03
Colon	6	rs62436418	167265792	G	A	593	0.6275	−3.161	1.57E−03
B2	6	rs9355610	167303065	A	G	592	1.433	2.709	6.75E−03	0.3608
Colon	6	rs9355610	167303065	A	G	593	0.7299	−2.04	4.14E−02

A1 = minor allele;
A2 = major allele

TABLE 5

RNASET2 SNPs Associated with CD and IBD. Major allele is risk for CD and IBD.

Pheno

type

CHR

SNP_rsid

BP

A1

A2

TEST

NMISS

OR

STAT

P

LOCATION

MAF

CD

6

rs2149085

167291100

G

A

ADD

4360

0.8414

−4.016

5.93E−05

INTERGENIC

0.4751

CD

6

rs1819333

167293537

C

A

ADD

4361

0.8446

−3.93

8.51E−05

INTERGENIC

0.4753

CD

6

rs3823208

167267836

G

A

ADD

4361

0.8507

−3.64

2.73E−04

INTRON

0.3446

CD

6

rs62436418

167265762

G

A

ADD

4361

0.8569

−3.539

4.01E−04

INTERGENIC

0.3861

CD

6

rs2769345

167286384

G

A

ADD

4361

0.8593

−3.53

4.15E−04

INTRON

0.4811

CD

6

rs9459813

167287827

A

T

ADD

4361

0.8028

−3.104

1.91E−03

INTRON

0.1102

CD

6

rs2236313

167280379

G

A

ADD

4361

0.8784

−3.016

2.56E−03

INTRON

0.4476

CD

6

rs9355610

167303065

A

G

ADD

4361

0.9084

−2.163

3.05E−02

INTERGENIC

0.3502

IBD

6

rs41269599

167267869

A

G

ADD

5110

0.844

−1.982

4.75E−02

INTRON

0.0635

A1 = minor allele;

A2 = major allele

TABLE 6

RNASET2 SNPs Associated with Subclinical Phenotypes of CD

PHENO

TYPE

CHR

RSID

BP

A1

A2

TEST

NMISS

OR

STAT

P

LOCATION

MAF

PDM

	6	rs3798303	167274358	G	A	ADD	2093	1.38	3.019	2.54E−03	INTRON	0.09853
Iritis	6	rs41269599	167267869	A	G	ADD	1436	2.806	2.973	2.95E−03	INTRON	0.06876
Iritis	6	rs181130555	167277010	D	—	ADD	1434	2.744	2.932	3.37E−03	INTRON	0.07108
Iritis	6	rs3777721	167272065	C	G	ADD	1436	2.761	2.92	3.50E−03	INTRON	0.07084
Iritis	6	rs41269597	167267663	C	G	ADD	1436	2.711	2.868	4.13E−03	INTRON	0.07234
Iritis	6	imm_6_167277028	167277028	A	—	ADD	1435	2.609	2.776	5.51E−03	INTRON	0.07369
Iritis	6	rs1079145	167280714	A	G	ADD	1436	2.424	2.717	6.59E−03	INTRON	0.0893
Iritis	6	rs10946197	167268406	A	C	ADD	1436	0.3753	−2.717	6.60E−03	INTRON	0.256
PDM	6	rs3777723	167273691	A	G	ADD	2093	1.334	2.648	8.09E−03	INTRON	0.09552

A1 = minor allele;
A2 = major allele;
D = deletion

TABLE 7

RNASET2 Associations with Subclinical Phenotypes in non-Jewish CD Patients

PHENO
TYPE	CHR	RSID	BP	A1	A2	TEST	NMISS	OR	STAT	P	MAF

Iritis

	6	rs1079145	167280714	A	G	ADD	680	3.646	2.99	2.79E−03	0.07357
Iritis	6	rs3777721	167272065	C	G	ADD	680	3.844	2.97	2.98E−03	0.05932
Iritis	6	rs181130555	167277010	D	—	ADD	679	3.622	2.909	3.63E−03	0.0613
Iritis	6	imm_6_167277028	167277028	A	—	ADD	679	3.511	2.848	4.40E−03	0.06168
Iritis	6	rs3778439	167278341	A	G	ADD	680	3.535	2.671	7.55E−03	0.05277
Iritis	6	rs3734246	167278058	A	G	ADD	680	3.535	2.671	7.55E−03	0.05277
PDM	6	rs2769339	167275844	G	A	ADD	977	1.553	2.929	3.41E−03	0.09707
PDM	6	rs2757045	167270953	G	A	ADD	977	1.499	2.73	6.34E−03	0.09977
PDM	6	rs3798303	167274358	G	A	ADD	977	1.491	2.669	7.62E−03	0.09669
PDM	6	rs2757048	167271110	A	G	ADD	977	1.479	2.637	8.37E−03	0.099
Uveitis	6	rs3777723	167273691	A	G	ADD	674	3.78	2.657	7.89E−03	0.09091

A1 = minor alele;
A2 = major allele;
D = deletion

TABLE 8

RNASET2 Association with Serologies in CD Patients

BETA/

Phenotype

CHR

SNP_rsid

BP

A1

A2

TEST

NMISS

OR

STAT

P

LOCATION

MAF

CBIR

	6	rs425145	167321292	G	A	ADD	2432	4.175	2.167	3.03E−02	INTERGENIC	0.1121
CBIR	6	rs415356	167326817	G	A	ADD	2432	4.16	2.164	3.06E−02	INTERGENIC	0.1121
CBIR	6	rs435359	167317604	G	A	ADD	2432	4.16	2.164	3.06E−02	INTERGENIC	0.1123
CBIR	6	rs375883	167304704	T	A	ADD	2430	4.119	2.14	3.24E−02	INTERGENIC	0.112
CBIR	6	rs62438869	167320907	A	G	ADD	2432	−3.722	−2.101	3.57E−02	INTERGENIC	0.1281
CBIR	6	rs9459813	167287827	A	T	ADD	2432	4.073	2.015	4.40E−02	INTRON	0.09872
CBIR	6	rs443297	167304286	A	G	ADD	2432	3.978	1.972	4.88E−02	INTERGENIC	0.09947
IgG.ASCA	6	rs1410295	167265493	C	G	ADD	2326	2.342	1.936	5.29E−02	INTERGENIC	0.3474

A1 = minor allele;
A2 = major allele

TABLE 9

RNASET2 Associations with Serologies of non-Jewish CD Patients

SEROLOGY	CHR	RSID	BP	A1	A2	TEST	NMISS	BETA	STAT	P	MAF

ANCA

	6	rs41269599	167267869	A	G	ADD	1143	−7.159	−2.709	6.85E−03	0.05586
CBIR	6	rs9459813	167287827	A	T	ADD	1208	8.021	2.854	4.40E−03	0.1159
CBIR	6	rs9459812	167287711	A	C	ADD	1208	7.699	2.735	6.33E−03	0.1156
IgA.ASCA	6	rs3823208	167267836	G	A	ADD	1130	4.153	3.102	1.97E−03	0.3139
IgG.ASCA	6	rs3823208	167267836	G	A	ADD	1130	4.99	3.115	1.89E−03	0.3139
IgG.ASCA	6	imm_6_167277028	167277028	A	—	ADD	1129	8.352	2.725	6.53E−03	0.06168

A1 = minor allele.
A2 = major allele

TABLE 10

RNASET2 Associations with Expression in Small Bowel

SNP_rsid	gene	beta	p-value	FDR

rs72079749	RNASET2	0.151129328	1.66E−04	0.371075825
rs66591848	RNASET2	0.154066135	2.27E−04	0.42289639
rs1951459	RNASET2	0.161888591	2.39E−04	0.429556929
rs4710149	RNASET2	0.161888591	2.39E−04	0.429556929
rs933243	RNASET2	0.161888591	2.39E−04	0.429556929
rs9355610	RNASET2	0.161888591	2.39E−04	0.429556929
rs9356551	RNASET2	0.161888591	2.39E−04	0.429556929
rs9366078	RNASET2	0.161888591	2.39E−04	0.429556929
rs1819333	RNASET2	0.15479148	3.22E−04	0.461149469
rs2013815	RNASET2	0.15479148	3.22E−04	0.461149469
rs2149085	RNASET2	0.15479148	3.22E−04	0.461149469
rs2769345	RNASET2	0.128393311	3.08E−03	0.777560209
rs2236313	RNASET2	0.096154247	3.09E−02	0.908151161

Major allele is risk for small bowel expression.

TABLE 11

RNASET2 Associations for Expression in Large bowel

	snp_rsid	gene	beta	t-stat	p-value	FDR

CD
Rectum	rs683571	RNASET2	−0.57902	−3.65206	0.00115	0.460077
Rectum	rs2031846	RNASET2	−0.48099	−3.27469	0.002992	0.679028
Rectum	rs62436763	RNASET2	−0.50894	−3.24339	0.003235	0.692932
Rectum	rs41463945	RNASET2	−0.58473	−3.11594	0.004434	0.693762
Sigmoid	rs162289	RNASET2	0.147287	2.955434	0.007311	0.619358
Sigmoid	rs162291	RNASET2	0.147287	2.955434	0.007311	0.619358
Sigmoid	rs162293	RNASET2	0.147287	2.955434	0.007311	0.619358
Sigmoid	rs162294	RNASET2	0.147287	2.955434	0.007311	0.619358
Sigmoid	rs162295	RNASET2	0.147287	2.955434	0.007311	0.619358
Sigmoid	rs162297	RNASET2	0.147287	2.955434	0.007311	0.619358
Sigmoid	rs2236312	RNASET2	0.162431	3.419281	0.002456	0.451404
Sigmoid	rs3756838	RNASET2	0.14602	3.147931	0.00467	0.576607
Sigmoid	rs3798307	RNASET2	0.162431	3.419281	0.002456	0.451404
Sigmoid	rs62436424	RNASET2	0.14602	3.147931	0.00467	0.576607
Sigmoid	rs7772112	RNASET2	0.14602	3.147931	0.00467	0.576607
Sigmoid	rs9366076	RNASET2	0.14602	3.147931	0.00467	0.576607
UC
Rectum	rs57237533	RNASET2	0.572002	3.665898	0.001643	0.436982
Rectum	rs56213919	RNASET2	0.572002	3.665898	0.001643	0.436982
Sigmoid	rs10946198	RNASET2	−0.36397	−3.11588	0.008192	0.704927
Sigmoid	rs1819333	RNASET2	−0.36397	−3.11588	0.008192	0.704927
Sigmoid	rs2149085	RNASET2	−0.36397	−3.11588	0.008192	0.704927
Sigmoid	rs2769345	RNASET2	−0.36397	−3.11588	0.008192	0.704927

TABLE 13

RNASET2 Exome CHIP

Function

Assoc

dis

SNP/rsID

n.case

n.ctrl

CHR

BP

A1

A2

MAF

NMISS

OR

P

geneList

GVS

Locus

CD

exm-

5742

5725

6

1.7E+08

G

A

0.4134

11467

0.8932

3.28E−05

RNASET2

intron

IBD

rs2236313

IBD

exm-

10523

5725

6

1.7E+08

G

A

0.4145

16248

0.9219

0.00061

RNASET2

intron

IBD

rs2236313

A1 = minor allele;

A2 = major allele

Allele risk is defined by the Odds ratio (OR). When the A1 allele and an OR of <1 is depicted, then the major allele is the risk allele (A2 is risk). If the OR is >1, then the minor allele (A1) is risk allele. Knowing A1 and the Odds Ratio allows you to determine which allele is risk and which is protective.

Example 2

The molecular mechanisms of TL1A augmentation of inflammation via enhanced IFN-γ expression were defined using RNAseq. CD4⁺ T cells were analyzed in untreated conditions or treated with IL12 and IL18 or IL12 and IL18 and TLA1 at the 1 ug scale. On a 10 ng scale, CD4⁺ T cells were analyzed when treated with IL12 and IL18 and TLA1, either with or without IFN-γ. The RNAseq data prescreen removed all failed probe data, all genes with fewer than 3 samples with FPKM>5. Using this criteria, 8695 genes passed the prescreen and BRB Array Tools were used for class comparison using paired samples.
The inventors demonstrate that at the molecular level, TL1A treatment mediates enhanced expression of IFN-γ, in addition to mediating a decreased expression of RNASET2. The decreased expression of RNASET2 is detected in CD patients: 1) with chronically active disease, 2) with refractive disease requiring surgical intervention, 3) with patients naïve to anti-TNF therapy, 4) is associated with OmpC+, ANCA− serological factors, and 5) is associated with RNASET2 risk SNPs rs9355610, rs1819333, rs2149085.

Example 3

TNFSF15 and the protein it encodes TL1A, is associated with IBD and are key mediators of mucosal inflammation. In IBD patients, elevated TL1A levels correlate with disease severity and genotype. TL1A mediates marked enhancement of IFN-γ production. TL1A response biomarkers were identified by RNAseq and verified by qPCR in T cells isolated from IBD patients (20 Crohn's [CD], 20 ulcerative colitis [UC]) compared to normal (NL). An additional cohort of samples from NL and IBD patients was used to validate and measure expression/methylation quantitative trait loci (eQTL/mQTL) in the context of GWAS. RNAseq expression clustering differentiated TL1A treated versus non-treated cells. RNASET2, a gene encoding an extracellular T2 RNase, was down-regulated following TL1A treatment. Previous studies associated RNASET2 with susceptibility for CD. RNASET2 expression in CD patients was lower in “severe” vs. mild disease, i.e., multiple disease flare-ups (p<0.009), medically refractory (p<0.024). Disease risk allele for RNASET2 rs1819333 (p=0.015) and TNFSF15 allele associated with enhanced TL1A expression, rs6478108, rs6478109 and rs7848647 (p=0.01) were correlated with decreased RNASET2 expression. Moreover, siRNA silencing of RNASET2 enhanced TL1A mediated IFN-γ secretion. Without being bound to any particular theory, the inventors believe that down-regulation of RNASET2 is a hallmark of TL1A driven severe CD.
RNASET2 expression and DNA methylation were examined in a separate cohort of freshly isolated un-stimulated T cells from NL, CD or UC patients. Methylation at RNASET2 locus inversely correlated with mRNA expression. eQTL of RNASET2 alleles was associated with decreased expression. Significantly enhanced RNASET2 methylation was observed in CD patients with severe disease requiring surgical intervention (Table 14). No correlation was observed in NL or patients with mild disease. Likewise, increased RNASET2 methylation was associated with TNFSF15 risk alleles associated with enhanced TL1A expression (Table 14). Epigenetically, the RNASET2 eQTL/mQTL region overlaps with histone H3K4me3 and H3K27ac and DNase HS activation sites. This region co-localizes with transcription factor binding for NFκB, jun, ATF3 and CEBPD—all of which are up-regulated in response to TL1A treatment. The results identify RNASET2 as a TL1A response gene involved in regulation of IFN-γ production. In CD patients with severe disease there is hyper-methylation and decreased expression of RNASET2, which may be reflective of prior exposure in-vivo to TL1A. Thus, without being bound to any particular theory, the inventors believe that RNASET2 serves as a novel potential disease severity biomarker to identify a subset of CD patients most likely to benefit from anti-TL1A therapy.

TABLE 14

Increased RNASET2 methylation associated with TNFSF15 risk allele.

RNASET2

TNFSF15

p value	rs62436418	rs2236313	rs2769345	rs1819333	rs9355610	rs6478108	rs6478109	rs7848647

eQTL	0.013	0.024	0.038	0.038	0.011	na	na	na
mQTL	0.001	2.7 × 10⁻¹³	2.7 × 10⁻¹³	2.7 × 10⁻¹³	1.4 × 10⁻⁹	0.005	0.013	0.003
(RNASET2)

The inventors further analyzed 3 cohorts of patients including 11 UC CD3⁺ PBT (medically refractive), 43 CD CD3⁺ PBT (23 were medically refractive and 20 were mild) and 17 normal CD3⁺ PBT. The samples were run on the Infinium 450 Methylation Array and 11 CD, 12 UC and 4 NL samples were run on the Infinium Expression Array. The inventors demonstrate that RNASET2 expression is decreased following TL1A treatment of CD4⁺ T cells and that silencing of RNASET2 enhances TL1A mediated IFN-γ secretion.

TABLE 15

Clinical Features

	Expres-	Methyla-
RNASET2	sion	tion

Multiple disease flares
Refractive disease requiring surgical intervention
Patients naïve to anti-TNF therapy
RNASET2 risk allele SNPs rs9355610, rs1819333,
rs62436418, rs22236313, rs2769345
RNASET2 risk allele SNPs
Refractive disease
Normal or Mild disease

Epigenetic studies demonstrated that RNASET2 eQTL/mQTL region overlaps with epigenetic activation sites for 1) histone H3K4me3 and H3K27ac, 2) DNase HS, 3) co-localizes with transcription factor binding for NFkB, jun, ATF3 and CEBPD, all of which are up-regulated in response to TL1A treatment. Furthermore, the enhancer element in primary T memory cells from peripheral blood, the DNAse HS site in CD4⁺ naïve T cells and the eQTL RPS6KA2 monocytes were linked to the rs1819333 allele.

Example 4

TL1A synergizes with IL-12/IL-18 resulting in a rapid (within 6-8 hours) and marked enhancement of IFN-γ expression. RNAseq analysis was used to identify the TL1A response genes regulating IFN-γ expression. Twenty genes were differentially expressed (at least 2-fold) in TL1A activated total CD4+ T cell population. This can be largely due to the fact that IFN-γ secreting T cells constitute only a very small subset (1-3%) of the total CD4+ T cell population (FIG. 15). CD4 T cells from healthy donors were treated with IL12/IL18 and TL1A for 8 hours and then sorted into IFN-γ-secreting and non-secreting subsets (FIG. 15) and whole-genome transcriptional analyses (GWAS) of mRNA was performed. Unsupervised hierarchical clustering of the entire 8075 expressed gene set clearly distinguished between the TL1A mediated IFN-γ-secreting and non-secreting subgroups (FIG. 16).
A class prediction analysis classifying the IFN-γ-secreting and non-secreting subgroups based on expression levels was performed. The best predictor transcript list consisted of 764 genes with at least two fold differential expression between the IFN-γ secreting subset (p-value<0.00005) (FIG. 17). Gene ontology analysis showed that the differentially expressed genes were enriched for those in pathways associated with proteasome, apoptosis, RNA expression and T cell receptor signaling, and were downstream targets of Infliximab (activation z score=−4, p value=2e-15). GWAS has identified multiple IBD risk variant SNPs. There was a significant increase in the proportion of transcripts located within 0.5 MB from an IBD risk SNPs (14% vs. 9%, p value=3.3e-6) compared to proportion of predictor genes in other regions. In fact, differentially expressed transcripts mapped to 34% of all IBD risk associated regions (FIG. 18). Without being bound to any particular theory, the data demonstrate a strong contribution for these genes not only in TL1A mediated modulation of IFN-γ expression but as contributing factors modulating IBD susceptibility and pathogenesis.
A volcano plot visualizing the significance and magnitude of differentially expressed predictor transcripts associated with IBD risk loci, allowed us to prioritize candidate genes (FIG. 20). Of these genes, TL1A mediated expression of IFN-γ was confirmed to be most significantly up-regulated and RNASET2 as most significantly down-regulated (FIG. 20). RNASET2, a member of the Rh/T2/S family of ribonuclease, was the only IBD risk associated gene displaying a greater than 5 fold TL1A mediated down-regulation in expression. RNASET2 has been identified by GWAS as a potential IBD risk gene. As the functional role of RNASET2 in IBD pathogenesis was unknown, the regulation of RNASET2 expression in IBD was examined. Without being bound to any particular theory, the inventors believe that since RNASET2 is a ‘class predictor’ gene, differential expression can be detected in total CD4+ T cells. Resting or IL12/IL18 treated CD4+ T cells from CD, UC patients or NL controls were isolated and RNASET2 levels were compared in the presence or absence of TL1A for 8 hours. As seen in FIG. 7, in contrast to what we had been observed in cells from NL donors, IBD patients did not display a TL1A mediated decrease in RNASET2 expression levels. Rather decreased expression levels of RNASET2 were associated in CD patients with “severe” compared to mild disease course. RNASET2 expression was significantly lower in cells isolated from CD patients exhibiting multiple disease flares per year (p<0.001) (FIGS. 8A and 8C) and likewise decreased RNASET2 expression was detected in CD patients who were medically refractive requiring surgical intervention for disease management (p<0.024) (FIG. 8B). A similar trend was seen in UC patients.
Gene expression quantitative trait (eQTL) was performed to characterize the functional correlation between RNASET2 gene variation and the gene transcript expression level. The IBD risk SNP tagging in Caucasians, rs1819333, and rs2149085 identified in the CD Korean population, are both located within −3.5 kb from the transcriptional start site, within the RNASET2 promoter region. An additional promoter SNP, rs9355610, has been shown to be associated with susceptibility with Grave's autoimmune thyroid disease. In peripheral cells isolated from CD patients the RNASET2 disease risk alleles rs1819333 (p=0.015) and rs2149085 (p=0.015), as well as, rs9355610 (p=0.04) display eQTL and were correlated with decreased RNASET2 expression (FIG. 9). Without being bound to any particular theory, the data indicates a pathway whereby down-regulation of RNASET2 alters IFN-γ expression. The functional role of RNASET2 in regulation of IFN-γ expression was confirmed using siRNA mediated silencing. CD4+ T cells were transfected with siRNA targeting RNASET2 mRNA or control siRNA and then treated with IL12/IL18 and TL1A. The expression of RNASET2 mRNA itself displayed a 60-70% inhibition by RNASET2 siRNA (FIG. 21A). In parallel, a significant enhancement (>1.5 fold) in IFN-γ expression was seen in cells transfected with RNASET2 siRNA compared to control scrambled siRNA (FIG. 21B).
Without being bound to any particular theory, the inventors believe that considering the pivotal role of IFNγ in pathogenesis of Crohn's disease these data collectively indicate that down-regulation of RNASET2 may serve as a biomarker of TL1A driven severe CD. RNASET2 expression was examined in a separate cohort of freshly isolated unstimulated T cells from NL, CD and UC patients. Since DNA methylation impacts upon gene expression and since most disease-risk genetic polymorphisms map outside of the transcribed exome in regions subject to epigenetic modification, the DNA methylation status of RNASET2 was examined as well. In unstimulated T cells from CD and UC patients an inverse correlation was observed between IFNγ expression levels and RNASET2 (FIG. 22). Moreover, as seen in FIG. 10, there was a significant negative correlation between expression and methylation which was inversely related to distance, mainly within 50 kb upstream and downstream from the transcriptional start site (TSS). Additionally, there was a significant overlap between IBD disease risk genetic variants and regions correlative for methylation and expression levels (FIG. 10). The strongest correlation (p=8.5×10⁻⁵) was observed at a CpG site (1.4 kb) within the first intron (FIG. 23).
The functional correlation between RNASET2 gene variation and the gene transcript expression level was confirmed in unstimulated peripheral T cells from IBD patients with refractory disease (FIG. 11), with decreased expression correlating with the RNASET2 risk allele variant SNP. Moreover, a similar eQTL was observed for mRNA extracted from tissue obtained from surgical resection of the small bowel using gene expression microarray (FIG. 12). The correlation between RNASET2 gene variation and methylation, mQTL was also examined and a significant mQTL was observed with an increase in methylation in IBD patients with refractory disease (FIGS. 13A-13D). In contrast, no mQTL was detected in cells isolated from patients with mild disease or NL subjects.
The role of these genetic variations affecting gene expression (eQTL) and DNA methylation (mQTL) was mapped across all informative SNPs spanning the RNASET2 locus (FIG. 14). In T cells isolated from IBD patients with medically refractory disease, there is strong overlapping eQTL and mQTL from 10 kb downstream of RNASET2 TSS to −170 Kb upstream, within the CCR6 locus. Likewise, there was a remarkable overlap in eQTL when comparing RNSASET2 expression from unstimulated peripheral T cells to small bowel surgical resection in patients with refractory disease. In contrast, in patients with mild disease or NL subjects no mQTL was detected (FIGS. 14A and 14B). This without being bound to any particular theory, the data suggests that down-modulation of RNASET2 is a component of TL1A mediated enhancement of IFN-γ expression. Additionally, epigenetic modulation of RNASET2 and reduced gene expression in IBD patients with a known IBD risk variant SNP is associated with a more severe course of disease.

Example 5

Methods

Peripheral T cells isolated from NL (normal) donors were cultured with or without TL1A for 8 hours. Gene expression profiling was performed by RNA sequencing (RNA-seq) and quantitative polymerase chain reaction (qPCR) using the subset of interferon gamma (IFN-γ)-producing cells purified by flow cytometry. Enzyme-linked immunosorbent assay (ELISA) and small interfering RNA (siRNA) inhibition and qPCR were used to measure the role of ribonuclease T2 (RNASET2) in TL1A mediated expression of IFN-γ. The role of RNASET2 in IBD was investigated using peripheral T cells isolated from IBD patients (20 CD and 20 UC) stimulated in a similar fashion. Findings were validated using additional samples of unstimulated T cells from NL and IBD patients or small bowel (SB) surgical resection and analyzed for expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL) based on genotyping and clinical data.
Screening for predicted motif disruption of transcription factor (TF) binding sites identified candidate regulatory SNPs. Proteomic analysis and measurement of cytokine secretion were used to determine effect of RNASET2-directed small interfering RNA (siRNA) on protein expression. Cell aggregation was measured by flow cytometry.

Study Subjects

Human subjects were recruited through the MIRIAD IBD Biobank at the F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute at Cedars-Sinai Medical Center. All control subjects were healthy individuals, free of medication, and with no known personal or family history of autoimmune disease or IBD. Informed consent (approved by the Institutional Review Board at Cedars-Sinai Medical Center) was obtained from all participating subjects. IBD patients were defined as “refractory” if surgical intervention was required for disease management following failure of medical therapy. IBD patients were defined as “mild” if they had no prior surgeries and no active disease at time of sample collection. CD patients exhibiting one or more disease flares per year were defined to have “severe disease” compared to patients with no disease flares per year. Clinical characteristics were prospectively collected from 564 CD patients who had undergone surgical resection.

Isolation of Lymphocyte Populations

Peripheral blood mononuclear cells (PBMC) were isolated from healthy volunteers by separation on Ficoll-Hypaque gradients. CD3⁺ T cells (PBT) were isolated using CD3-immunomagnetic beads (Miltenyi Biotech, Auburn, Calif.) and were at least 95% pure. CD4⁺ T cells were isolated using negative selection by depletion with magnetic beads (Stemcell Technologies, Vancouver, BC, Canada) and were at least 95% pure.

Infinium 450K Bead Chip Assay

DNA samples from CD3⁺ T cells were bisulfite converted using the Zymo EZ DNA Methylation kit (Zymo Research) with an input of 1 μg. The assay was carried out as per the Illumina Infinium Methylation instructions, using the Infinium HumanMethylation450 BeadChip Kit (Illumina Inc., San Diego, Calif.). Data were visualized and normalized using the GenomeStudio software. The methylation β values were recalculated as the ratio of (methylated probe signal)/(total signal).

IFN-γ Assay

IFN-γ was measured by an amplified ELISA. Greiner Bio-One (Longwood, Fla.) ELISA plates were coated overnight with 100 μl of 5 μg/ml monoclonal anti-IFN-γ (BD Biosciences, Woburn, Mass.). Samples and standards were added for 24 h followed by addition of 100 μl of 2.5 μg/ml polyclonal biotinylated rabbit anti-IFN-γ (BD Biosciences) for 2 h. This was followed by addition of 100 μl of 1/1000 diluted alkaline phosphatase-conjugated streptavidin (Jackson ImmunoResearch Laboratories, West Grove, Pa.) for 2 h. Substrate, 0.2 mM NADP (Sigma-Aldrich, St. Louis, Mo.) was added for 30 min followed by addition of amplifier (3% 2-propanol, 1 mM iodonitrotetrazolium violet, 75 μg/ml alcohol dehydrogenase, and 50 μg/ml diaphorase; Sigma-Aldrich) for 30 min. Plates were read at 490 nm using an E max plate reader (Molecular Devices, Sunnyvale, Calif.).

Gene Expression Assay for CD3⁺ T Cells

Expression analysis of CD3⁺ T cells was performed using the Illumina genome-wide expression BeadChip (HumanHT-12_V4_0_R2) (Illumina) or Nugen human FFPE RNA-seq library system. Illumina Gene expression data were processed using the BRB array tools and the lumi package in R. The data were log₂-transformed and normalized using robust spline normalization. Libraries for RNA-Seq were prepared with Nugen human FFPE RNA-seq library system. The workflow consists of cDNA generation, fragmentation, end repair, adaptor ligation and PCR amplification. Different adaptors were used for multiplexing samples in one lane. Sequencing was performed on Illumina NextSeq 500 for a single read 75 run. Data quality check was done on Illumina SAV. Demultiplexing was performed with Illumina Bcl2fastq2 v 2.17 program. The reads were first mapped to the latest UCSC transcript set using Bowtie2 version 2.1.0 and the gene expression level was estimated using RSEM v1.2.15. FPKM was used to normalize the gene expression.
siRNA Inhibition and Quantitative Proteomic Analysis
Freshly isolated CD4⁺ T cells (15×10⁶) were cultured overnight in RPMI 1640 medium containing 10% fetal calf serum, washed, resuspended in 250 μL fresh medium, and electroporated in the presence of 150 pmole of RNASET2 siRNA or control siRNA (600 V, for 9 pulses of 500 μsec, with 100 μsec between pulses) using 4 mm (gap width) cuvettes in a BTX Electro Square Porator ECM 830 (Genetronics, Inc., San Diego, Calif.). Sequences used in siRNA inhibition are depicted in Table 16.

TABLE 16

siRNA sequences

		SEQ
Sequence Name	Sequence	ID NO

RNASET2 siRNA-sequence forward	5′-GCAAGAGAAAUUCACAAACUGCAGC-3′	7

RNASET2 siRNA-sequence reverse	5′-GCUGCAGUUUGUGAAUUUCUCUUGCUU-3′	8

Control siRNA-sequence forward	5′-CUUCCUCUCUUUCUCUCCCUUGUGA-3′	9

Control siRNA-sequence reverse	5′-UCACAAGGGAGAGAAAGAGAGGAAGGA-3′	10

Tandem mass tagging (TMT)-based quantitative proteomics analysis was conducted as described (Qu et al., Sci Rep 2016; 6:32007). For each sample, 50 μg proteins were digested in parallel into tryptic peptides using filter-aided sample preparation (FASP) (Wisniewski et al., Nat. Methods 2009; 6:359-62). Peptides derived from eight samples and a pooled internal standard were labeled with a set of TMT10plex reagents (Thermo Scientific), mixed, desalted, separated into 24 fractions by high-pH liquid chromatography, and concatenated into 8 fractions. Fractionated peptides were resolved on a 50 cm EASY-Spray analytical column, and analyzed by an LTQ Orbitrap Elite mass spectrometer (Thermo Scientific) in the data-dependent acquisition mode, using the higher-energy collisional dissociation (HCD) method for tandem mass spectrometry. Acquired raw data were searched against the human Uniprot database (released on Oct. 17, 2015, containing 20,982 sequences) with Proteome Discoverer (v2.1), using the SEQUEST algorithm. A stringent 1% false discovery rate was set to filter peptide and protein identifications. Peptides with >30% precursor ion interference were excluded from protein quantification.

Flow Cytometry and Analysis of Cellular Aggregation

IFN-γ-secreting CD4⁺ T cells was isolated by flow cytometry following activation of cells with recombinant human IL-12 (500 pg/ml, R&D Systems, Minneapolis, Minn.) and IL-18 (50 ng/ml, R&D Systems) and TL1A (100 ng/ml, Fitzgerald Industries International, Acton, Mass.) for 8 h. IFN-γ-secreting CD4⁺ T cells were detected using an IFN-γ secretion assay cell enrichment and detection kit (Miltenyi Biotec, San Diego, Calif.). Cells were sorted on a FACS Aria II (BD Biosciences, San Jose, Calif.).
Intracellular IFN-γ production and analysis of cellular aggregation was conducted essentially as described (Dezorella et al., Cytometry B Clin Cytom 2016:90:257-66) Briefly, cells were either rested or stimulated for 24 h with IL12/IL18 and TL1A and Berfeldin A (10 ug/ml) was added for the last 4 h. Cells were fixed with 4% paraformaldehyde, permeabilized with 0.1% Triton X-100 and 0.2% saponin and stained for intracellular IFN-γ (brilliant violet 421-IFN-γ, eBioscience) or isotype control. Samples were washed and stained for cellular aggregation (propidium iodide). Cells were acquired on a CyAnTM ADP Flowcytometer (Dako, Carpinteria, Calif., USA) and analyzed with FlowJosoftware (TreeStar Inc., Ashland, Oreg., USA). For LFA1 blocking analysis cells were pre-incubated overnight in conical microplates with monoclonal control mouse IgG1k (15 ug/ml) or anti-LFA1 (TS1/18) followed by stimulation with IL12, IL18 and TL1A for 24 h.
qPCR
Total RNA was isolated using the RNeasy kit (Qiagen, Inc., Valencia, Calif.) and gene expression was measured by real-time quantitative RT-PCR. Five hundred nanograms of total RNA were used in each RT-PCR reaction, with oligo (dT) (Integrated DNA Technologies) as primer, using the Omniscript kit and protocol (Qiagen). Real-time PCR was performed using a Mastercycler® ep realplex PCR detection system (Eppendorf, Hauppauge, N.Y.). PCR assays were run in duplicate. Primer sequences (Integrated DNA Technologies) spanned introns and are depicted in Table 17.

TABLE 17

Primer sequences

		SEQ
		ID
Sequence Name	Sequence	NO

IFN-γ forward	5′-TTGGGTTCTCTTGGCTGTTACT-3′	11

IFN-γ reverse	5′-ATCCGCTACATCTGAATGACCTG-3′	12

RNASET2	5′-CTTCCTTGCAGGACTCACCAC-3′	13
forward

RNASET2
	5′-GCTGATGTGAAGGTGCAAACTC-3′	14
reverse

ACTB forward	5′-CGTGCTGCTGACCGAGG-3′	15

ACTB reverse	5′-AAGGTCTCAAACATGATCTGGGT-3′	16

Genotyping

Genotype data was obtained for Caucasian subjects using Illumina HumanImmuno BeadChip array. Markers were excluded based on: test of Hardy-Weinberg Equilibrium with significance threshold of p≤10⁻³; if genotyping rate was <100% (for eQTL and mQTL associations) or <98% (for GWAS) and if minor allele frequency was <5%. Identity-by-descent was used to exclude related individuals (Pi-hat scores >0.25) using PLINK. ADMIXTURE was used to perform ethnicity analysis to get ethnicity proportion estimation for individuals. An individual with Caucasian proportion ≥0.75 was classified as Caucasian. Independent Caucasian samples were identified based on relatedness check (using cut-off pi-hat scores) and ethnicity analysis from admixture and all subsequent associations were performed using these samples. Principal components in genotype data for independent Caucasian samples were generated using TRACE. LDHeatmap R package was used to generate LD plot for the SNPs in RNASET2 locus using genotype data for 139 subjects. Details of the QC and genotyping in IIBDGC cohort can be found in previous reports (Jostins et al., Nature 2012; 491:119-24 and Liu et al., Nat Genet 2015; 47:979-86). In brief, 18,602 CD cases and 33,938 non-IBD controls genotyped using ImmunoChip were included in the analysis after samples with >5% missing data, samples of non-European ancestry from population stratification or with abnormal mean intensity values, and SNPs with >2% missing data or HWE p-value <10⁻¹⁰in controls were removed. Of the CD cases from IIBDGC, 13,511 have disease behavior information collected based on Montreal classification as reported previously (Cleynen et al., Lancet 2016; 387:P156-67) (described as B1, non-stricturing, non-penetrating, B2, stricturing and B3, penetrating diseases).

Expression Data for Small Bowel Surgical Samples

Single channel microarray expression data extracted using Agilent feature extraction software were received from Genome Technology Access Center at Washington University, St. Louis. Raw expression data available in technical duplicates were normalized using LIMMA package implemented in R version 3.2.2. The expression data preprocessing included background correction of the expression data, followed by log 2-transformation and quantile-normalization.
EQTL and mQTL Mapping
eQTL and mQTL mapping was implemented in Matrix eQTL R package. For small bowel surgery samples, eQTL mapping was done using independent Caucasian samples (n=85). Associations between genotype and probe expression level (for eQTL) or methylation β values (for mQTL) were performed using a linear regression model with additive genotype effects. All associations were conducted with gender and first two principal components in genotype data as covariates along with genotype. Around 200 genetic variants within 200 KB of RNASET2 TSS were used to perform associations with RNASET2 gene expression or methylation levels.

Motif Analysis and Identification of Candidate Regulatory SNPs

All variants exhibiting eQTL and mQTL were analyzed for predicted disruption of TF binding motifs using the bioconductor motifbreakR package (Coetzee et al., Bioinformatics 2015; 31:3847-9). Only T cell specific TFs identified as being expressed using RNAseq data from CD patients, were carried forward. Candidate regulatory SNPs were then analyzed for potential functionality based on Roadmap Epigenomics Mapping Consortium (REMC) data (Roadmap Epigenomics C. et al, Nature 2015; 518:317-30). Potential active enhancer regions were determined based on overlap of the histone modification H3K4me1 with H3K27ac signals (Coetzee et al., Hum Mol Genet 2015; 24:3595-607). Potential functionality of TF regulation was determined based on REMC CHIP-seq binding signal and Regulome data.

Pathway Analysis

Pathway analysis was accomplished through the use of Qiagen's Ingenuity® Pathway Analysis (IPA®, Qiagen, Redwood City, www.qiagen.com/ingenuity) and The Database for Annotation, Visualization and Integrated Discovery (DAVID, http://david.abcc.ncifcrf.gov).

Statistical Analysis

Modeling, data analysis, and data mining were performed using the BRB array tools (brb.nci.nih.gov/BRB-ArrayTools) and R-program (version 2.2.2; www.r-project.org). Class prediction analysis used compound covariate predictor, diagonal linear discriminant analysis, k-nearest neighbor (using k=1 and 3), nearest centroid, and support vector machines, based upon a minimum p value of 0.001. Cluster analysis was performed using Cluster 3.0 and Java Treeview 1.1.6r4. Tests for statistical significance were determined using JMP Statistical Software (Cary, N.C.). Test for clinical association between of rs1819333 and rs9355610 SNPs and therapeutic failure, ANCA sero-positivity, resected bowel length and time to reoperation were calculated by parametric Student's T test and Pearson correlation; test of association and trend using Fisher's exact test and Kaplan-Meier Survival Curves. Association with endoscopic recurrence was calculated by Cochran-Armitage trend test.

Results

In this study, the inventors identified down-modulation of RNASET2, an IBD susceptibility gene, as a component of TL1A-mediated enhancement of cytokine production and as a novel potential biomarker of disease severity. Down-regulation of RNASET2 following siRNA silencing resulted in increased IFN-γ secretion, without being bound to any particular theory, supporting a role in regulating inflammatory response. A decrease in RNASET2 expression was also observed in peripheral T cells from CD patients with one or more yearly disease flares compared to patients with no yearly disease flares. Functionally, quantitative trait loci were associated with RNASET2 disease-risk variants for decreased expression (eQTL) in peripheral and mucosal tissues and DNA hypermethylation (mQTL) from CD patients with medically refractory, but not mild disease. Additionally, RNASET2 disease-risk variants were associated with an increase in development of stricturing/penetrating disease behavior. Furthermore, RNASET2 disease-risk variants were associated with a complicated/resistant CD phenotype defined in part by therapeutic drug failure, ANCA sero-positivity, increased length of intestinal resection, shorter time to reoperation and post-operative endoscopy with a high (>2) Rutgeerts score. Motif screening of RNASET2 disease-risk variants identified rs2149092 with predicted disruption of a consensus ETS-TF binding site located within a potential enhancer region, providing insight into RNASET2 cis-regulatory elements. RNASET2 correlated with expression of multiple ETS-transcription factors. Finally siRNA silencing of RNASET2 resulted in enhanced IFN-γ, increased ICAM1 and concomitant T cell aggregation while anti-LFA1 blocking of aggregation suppressed IFN-γ secretion.
Identification of Differential Gene Expression Associated with TL1A Mediated Enhancement of IFN-γ Production
To identify the underlying molecular pathways involved in TL1A-mediated enhancement of IFN-γ production, a key IBD proinflammatory cytokine, CD4⁺ T cells were treated with TL1A, sorted into IFN-γ-secreting and non-secreting subsets and analyzed by RNA-seq (FIG. 15 and FIG. 27). Unsupervised hierarchical clustering of the set of expressed genes clearly distinguished TL1A-mediated IFN-γ-secreting and non-secreting groups (FIG. 16). Seven hundred and sixty-four “predictor” genes with at least two-fold differential expression between the IFN-γ secreting/non-secreting subsets (p value <1×10⁻⁵) (FIG. 17) were identified. Gene ontology analysis indicated that differentially expressed genes were enriched in pathways associated with T cell receptor signaling, apoptosis, and RNA expression, and were downstream targets of infliximab, an anti-TNF biologic drug. Predictor genes were significantly enriched in regions flanking GWAS identified IBD susceptibility variants (0.25 MB upstream or downstream of the single nucleotide polymorphism (SNP) compared to other regions (14% vs. 9%, p value is 3.3×10⁻⁶, hypergeometric test). Without being bound to any particular theory, these data suggest that these genes contribute not only to TL1A-mediated modulation of IFN-γ expression, but also overlap with IBD risk-associated loci. Of the IBD-risk associated predictor genes, expression of IFN-γ was confirmed as the most significantly upregulated and RNASET2 as the most significantly down regulated gene (FIG. 20). RNASET2 was the only IBD risk associated gene with greater than 5-fold down regulation in the IFN-γ secreting CD4⁺ subset.
RNASET2 Regions Displaying Inverse Correlation of Expression and DNA Methylation Levels Overlap with Regions Flanking Disease-Risk Associated Variants
RNASET2 is the only human member of the Rh/T2/S family of ribonucleases and its expression is decreased in ovarian cancer, melanoma and non-Hodgkin lymphoma. Considering the key role for IFN-γ in pathogenesis of Crohn's disease/IBD, without being bound to any particular theory, these data collectively suggest that down regulation of RNASET2 identifies TL1A mediated ‘severe’ CD. RNASET2 expression was examined in freshly-isolated, unstimulated peripheral CD3⁺ T cells from a separate cohort of NL, CD and UC patients. Since DNA methylation is understood to be one of the mechanisms that impacts gene expression, particularly in disease-associated genetic variants that map outside transcribed exomes, we examined the DNA methylation status across the RNASET2 locus. RNA-seq analysis demonstrated there was an inverse correlation between TNFSF15 expression levels and RNASET2 in peripheral T cells from two independent cohorts comprised of a combined 138 CD patients (FIGS. 24A and 24D). These results were consistent even when each cohort was analyzed separately (FIGS. 24B and 24C). Moreover, there was a significant negative correlation between expression and methylation (FIG. 23), mainly within 50 kb upstream and downstream from the transcriptional start site (TSS) (FIG. 26). The strongest correlation of methylation and expression (p=8.5×10⁻⁵) was observed at a CpG site (1.4 kb) within the first intron of RNASET2 (FIG. 26). Additionally, CD disease genetic risk variants, including the IBD risk SNP tagging the RNASET2 locus in European ancestry populations, rs1819333, overlapped with regions correlative for methylation and expression levels (FIG. 10).
RNASET2 Disease-Risk Alleles are Associated with Decreased RNASET2 Expression and Increased DNA Methylation in CD Patients with Refractory Disease
Gene expression quantitative trait (eQTL) was performed to characterize the functional correlation between RNASET2 gene variation and the gene transcript expression level. The disease associated SNPs for IBD risk in Europeans, rs1819333, and Koreans, rs2149085, as well as the risk SNP associated with Graves' disease, rs9355610, are located −13 kb from the transcriptional start site of RNASET2. The functional correlation between RNASET2 IBD-risk genotypes and the gene transcript expression levels were established in unstimulated peripheral CD3⁺ T cells isolated from IBD patients with refractory disease. The data demonstrated significantly decreased RNASET2 expression in T cells from subjects carrying the RNASET2 risk alleles rs2149085, rs1819333, and rs9355610 (FIG. 11). These findings were confirmed with significant eQTL observed for mRNA extracted from uninflamed small bowel tissue obtained from CD subjects at surgical resection (FIG. 12). The correlation between RNASET2 gene variation and methylation, mQTL was also examined. A significant mQTL was observed with an increase in methylation in CD patients with refractory disease (FIGS. 13A and 13C). In contrast, no mQTL was detected in cells isolated from CD patients with mild disease or NL subjects (FIGS. 13B and 13D). Moreover, there was a significant increase of complicated disease behavior, stricturing/penetrating phenotype (Montreal classification B1 vs. B2 and B3), associated with CD patients carrying the RNASET2 disease risk SNPs (rs1819333/rs2149085 p=0.05, rs9355610 p=0.01).
Gene expression (eQTL) and DNA methylation (mQTL) was mapped across all informative SNPs spanning the RNASET2 locus (LD plot). In T cells isolated from patients with medically refractory disease, there is strong overlapping eQTL and mQTL from 10 kb downstream of RNASET2 TSS to −170 kb upstream, spanning fibroblast growth factor receptor 1 oncogene partner (FGFR1OP) to the first intron of chemokine (C—C motif) receptor 6 (CCR6). Likewise, there was overlap in eQTL when comparing RNASET2 expression from unstimulated peripheral T cells to small bowel surgical resection in CD patients with refractory disease. In contrast, few mQTL associations were detected in CD patients with mild disease or NL subjects (FIGS. 14A and 14B). No eQTL association was detected for FGFR1OP or CCR6. These data were further validated in a separate cohort of peripheral T cells isolated from CD patients with medically refractory disease. There was significant overlap between RNASET2 risk variants associated with CD and corresponding eQTL (FIG. 28) which, without being bound to any particular theory, suggest a functional role for RNASET2 in mediating disease.

Attenuated Expression of RNASET2 in CD

To establish a role for RNASET2 in IBD pathogenesis, regulation of RNASET2 expression in CD4⁺ T cells isolated from IBD patients was examined and compared to normal (NL) donors in the presence or absence of TL1A. As seen in FIG. 7, NL donors, but not IBD patients, exhibited a TL1A-mediated decrease in RNASET2 expression levels. Instead, decreased expression levels of RNASET2 were found in CD patients with more severe disease (exhibiting one or more disease flares per year) compared to patients with no yearly disease flares (FIGS. 8A and 8C).
RNASET2 Disease Risk Alleles are Associated with Complicated and Resistant Disease Behavior
To evaluate the association between RNASET2 and disease activity and severity the inventors utilized a cohort of 564 CD patients who had undergone surgical resection and were then followed prospectively. Clinical characteristics including indication for surgery were assessed for association with RNASET2 risk variants (rs1819333 and rs9355610). RNASET2 disease risk variant SNPs were associated with a complicated stricturing/penetrating phenotype (Montreal classification B1 vs. B2 and B3), (Table 18). At the time of surgery, patients with RNASET2 disease risk variant SNPs were associated with therapeutic failure of thiopurine or anti-TNF therapy, ANCA sero-positivity (a marker associated with lack of response to anti-TNF therapy), and an increased length of intestinal resection characteristic attributed to overall disease severity (Table 18 and FIGS. 38-39). No association was observed for therapeutic failure on steroids or sulfasalazine. Moreover, patients with RNASET2 disease risk variant SNPs who required multiple resections for disease management exhibited a shorter time to reoperation (FIG. 32).

TABLE 18

Clinical disease parameters associated
with RNASET2 risk variants.

rs1819333

rs9355610

Clinical parameter	p	OR	p	OR

Disease Behavior
B2 vs. B1^a	ns	ns	0.041	1.07
B3 vs. B1^a	ns	ns	0.056	1.06
B2, B3 vs. B1^a	0.051	1.05	0.016	1.07
Therapeutic failure of thiopurine^b	0.009	1.68	0.019	1.75
Therapeutic failure of anti-TNF^b	0.039	1.46	0.042	1.56
ANCA sero-positivity^b	0.009	2.24	0.047	2.07
Resected segment >30 cm^b	ns	ns	0.004	2.13
>40 cm^b	ns	ns	0.031	1.96

Endoscopic recurrence Rutgeert's
score 3-4 vs 1-2	p	z score	p	z score

No prophylactic meds^b	0.025	2.24	0.024	2.25

^aIIBDGC cohort CD (n = 3345)/case control (n = 6277)
^bCD patients (n = 584) who had undergone surgical resection and followed prospectively.

Likewise, RNASET2 risk SNPs were associated with a more severe disease recurrence. Post-operative endoscopies revealed an association of RNASET2 risk SNPs in patients classified with a high Rutgeerts score (>2) who were not receiving postoperative prophylaxis (Table 18). No association was observed for clinical recurrence. Decreased expression of RNASET2 was also associated with a penetrating disease phenotype (FIG. 31) and ASCA sero-positivity (FIG. 30). Without being bound by any particular theory, this data supports an association of RNASET2 disease risk SNPs with clinical parameters suggestive of complicated and resistant disease behavior.
RNASET2 Variant in LD with Disease-Tagging SNP Disrupts ETS Transcription Factor Binding Motif
The data presented above demonstrate significant overlap between more than a hundred CD RNASET2 risk variants, many in linkage disequilibrium, associated with eQTL and mQTL creating difficulty in determining functionality/causality. Since the majority of RNASET2 risk variants associated with CD are located in non-coding regions, it is likely that these SNPs alter expression through modulation of regulatory functions. Furthermore, without being bound to any particular theory, studies suggest that SNPs associated with disease often exist within active enhancer regions of cell types relevant to disease and can disrupt TF binding motifs. REMC data demonstrate that the RNASET2 locus is marked in primary T cells, compared to other tissues, by putative active enhancer histone modifications and active gene expression (FIG. 40). To gain insight into the molecular pathways regulating RNASET2 expression and prioritize the number of candidate functional SNPs, the inventors performed motif analysis to predict TF motif disruptions across all SNPs which were associated with eQTL/mQTL. Variants disrupting motifs of TFs expressed in T cells were selected and candidate variants in LD with the RNASET2 disease index SNP rs1819333 were focused on. The rs2049092 SNP disease risk variant, located −569 bp from the index SNP (LD R2=1), lies within the highly conserved TTCC motif, utilized by most ETS transcription factors, and is predicted to disrupt TF binding. Sequence analysis demonstrates an overlap of IRF4 and Spi1 binding sites adjacent to a JUN binding site (FIG. 36A). Regulome and REMC data confirm TF occupancy of ETS1, IRF4 and Spi1 binding in lymphoblastoid cell lines (FIG. 36B) which overlaps with histone modifications indicative of an active enhancer element. Moreover, there is a strong correlation between expression of RNASET2 with multiple members of ETS and JUN TF (FIGS. 36C and 41). No correlation was observed for IRF4 (FIG. 41). Without being bound to any particular theory, these data strengthen the relevance of RNASET2 expression in the immune compartment and support a functional role for ETS and JUN transcription factors in regulating transcription of RNASET2.

Silencing of RNASET2 Enhances IFN-γ Secretion Via Upregulation of ICAM1 Expression and Homotypic T Cell Aggregation

The functional role of RNASET2 in regulation of IFN-γ secretion was tested using siRNA silencing. CD4⁺ T cells transfected with siRNA targeting RNASET2 mRNA followed by stimulation with TL1A. Cells transfected with siRNA targeting RNASET2 displayed a 60-70% inhibition of RNASET2 expression (FIGS. 21A and 37A), and a parallel significant enhancement (>1.5 fold) in TL1A mediated IFN-γ secretion was seen compared to control siRNA (FIG. 21B and FIG. 37B). Without being bound to any particular theory, these data suggest that down regulation of RNASET2 modulates IFN-γ expression.
In order to define the signaling pathways involved in this process, proteomic analysis was carried out. Candidate targets were selected on the basis of exhibiting both modulation of expression following siRNA silencing of RNASET2 as well as TL1A-mediated differential expression when comparing IFNγ secreting and non-secreting T cells (data from RNAseq analysis). One of the proteins that was up-regulated in response to RNASET2 silencing and in the IFNγ secreting compared to non-secreting T cells, was ICAM1 (FIG. 42). ICAM1 was recently identified as an IBD susceptibility locus, with up-regulated gene expression associated with the disease-risk variant. ICAM1 is a transmembrane adhesion protein commonly expressed by vascular endothelium and leukocytes. Binding of ICAM to the LFA1 receptor on T cells facilitates and stabilizes cell-cell interactions. Studies have demonstrated increased ICAM1 expression on activated T cells and proposed a role for ICAM1-LFA1 binding in inducing homotypic T cell aggregation and subsequent T cells differentiation. To examine the effect of cell-cell contact on TL1A mediated IFN-γ secretion, cells were incubated in flat bottom and conical bottom microwells. A greater than 3 fold increase in IFN-γ production was consistently observed when cells were incubated in close cell-cell conical geometry (data not shown). Flow cytometry was then used to test the hypothesis that TL1A mediated enhancement of IFN-γ production is facilitated by homotypic T cell aggregation. Briefly, T cells were stimulated in the presence or absence of TL1A and then stained with an antibody for intracellular IFN-γ (FIGS. 37C and 37D, left panels) and for cellular aggregation using propidium iodide (PI) (FIGS. 37C and 37D, upper and lower right panels). The PI-labeled peaks correspond to number of cells per event allowing for identifying single cells versus cellular aggregates. The first peak in each histogram corresponds to single cell events (black brackets) and the successive peaks, to multicellular aggregates (gray brackets). Only a small percentage of the unstimulated T cells secreted IFN-γ, and these cells were almost equally distributed as single cell events and cellular aggregates (FIG. 37E, left panel). Following TL1A stimulation, there was a significant increase in both the percentage and size of cellular aggregates (upper right panels of FIG. 37C compared to FIG. 37D, as well as, the overall number of IFN-γ producing cells (6-fold) (FIGS. 37E and 37F) and a 30-fold increase in IFN-γ secretion (data not shown). In contrast, the majority of T cells that do not produce IFN-γ, are comprised of single cell events regardless of whether they were cultured with or without TL1A stimulation (FIG. 37E, right panel). Without being bound to any particular theory, these results suggest that cellular aggregation may contribute to both an increase in the number of cells producing IFN-γ and to overall amount of IFN-γ production, and TL1A stimulation may enhance this process. The functional role of TL1A in mediating cellular aggregation via ICAM1-LFA1 engagement was tested using an LFA-1 blocking antibody. As seen in FIG. 37G, there was an overall 43% reduction in IFN-γ secretion in response to blocking LFA-1 engagement, compared to IgG control antibody (p value=0.047). Without being bound to any particular theory, taken together these data indicate that TL1A-mediated downregulation of RNASET2 and concomitant enhancement of ICAM1 expression, promotes homotypic T cell aggregation and augmentation of IFN-γ production. It is noted that an increase in expression of ICAM1 was associated in CD with ASCA sero-positivity and pre-op therapeutic failure of anti-TNF and thiopurine (FIG. 43), clinical parameters associated with decreased RNASET2 and disease activity.

Example 6

Both RNASET2 and TNFSF15 have been identified among the 201 GWAS IBD susceptibility loci. TL1A, the protein encoded by TNFSF15, is a key mediator of mucosal inflammation. Elevated TL1A levels correlate with TNFSF15 genotype and disease severity. The inventors have identified that TL1A down regulates expression of RNASET2 in T cells. TNFSF15 and RNASET2 expression is inversely correlated in T cells from CD patients (p=5×10⁻¹⁶). The potential of RNASET2 as an IBD prognostic biomarker was examined.
The role for RNASET2 disease associated SNPs in IBD was analyzed by examining expression and methylation quantitative trait loci (eQTL/mQTL) in peripheral T cells from patients undergoing surgery (n=21) and small bowel surgical samples (n=85). CD patients (n=584) who had undergone surgical resection were followed prospectively. Clinical characteristics including indication for surgery were assessed for association with RNASET2 risk variants (rs1819333 and rs9355610).
RNASET2 disease associated SNPs were correlated with decreased RNASET2 expression (eQTL) in peripheral and mucosal tissues (p<0.001) and DNA hypermethylation (mQTL) (p<0.001) in patients requiring surgical intervention for disease management compared to those who were responsive to IBD therapeutics (n=16). RNASET2 disease associated SNPs were associated with therapeutic failure of thiopurine (p=0.02, OR=1.7) or anti-TNF therapy (p=0.04, OR=1.59), ANCA sero-positivity (a marker associated with lack of response to anti-TNF therapy) (p=0.02, OR=2.27), and an increase in overall length of intestinal resection (>30 cm p=0.004, OR=2.13/>40 cm p=0.03, OR=1.96). Patients with RNASET2 disease associated SNPs exhibited a shorter time to reoperation (p=0.04, z score=2.16). Post-operative endoscopies (n=369) with a high Rutgeerts score (>2) were associated with RNASET2 risk SNPs in patients not receiving post-op prophylaxis (p=0.02, z score=2.56) or those on anti-TNF therapy alone (p=0.03, z score=2.46), whereas no association was detected for patients on other IBD therapeutics.
This study identifies functional consequences of RNASET2 disease associated SNPs that are associated with clinically relevant disease behavior. RNASET2 risk SNPs were associated with clinical parameters suggestive of a complicated and resistant disease behavior. Moreover, response to therapeutics following surgery and recurrence of disease were associated with RNASET2 risk SNPs. Without being bound to any particular theory, these results taken together with our previous findings indicate that regulation of RNASET2 may underlie disease pathology triggered by TL1A and serve as a disease biomarker identifying subjects not responsive to current treatment strategies who may benefit from alternate therapeutic approaches.

Example 7

TABLE 19

Clinical features associated with RNASET2 disease risk SNPs

rs1819333

rs9355610

CD phenotype at Time of Surgery	p	OR	p	OR

therapeutic failure of thiopurine	0.009	1.68	0.019	1.75
therapeutic failure of anti-TNF	0.039	1.46	0.042	1.59
ANCA sero-positivity	0.009	2.24	0.047	2.07
Length of resected segment >30 cm			0.004	2.13
>40 cm			0.031	1.96
Family history of disease	0.030	1.58	0.030	1.78

CD patients (n = 584) who had undergone surgical resection and followed

prospectively

B2 vs B1			0.041	1.07
B3 vs B1			0.056	1.06
B2, B3 vs B1	0.051	1.05	0.016	1.07

IIBDGC cohort CD (n = 7173)/case control (n = 6278)

TABLE 20

Endoscopic Recurrence

Endo-		3-year clinical
scopic		recurrence rate
score	Definition	(%)

0	No lesions	5
1	≤aphtous lesions	5
2	apthous lesions with normal mucosa between	15-20
	the lesions, or skip areas of larger lesions
	or lesions confined to ileocolonic anastomosis
3	Diffuse apthous ileitis with diffusely	40
	inflamed mucosa
4	Diffuse inflammation with already larger	90
	ulcers, nodules, and/or narrowing

Adapted from Remedica Journals

Post-op

rs9355610

Endoscopic recurrence Rutgeert's score 3-4 vs 1-2	p	z score

No prophylactic meds	0.040	2.25
Anti-TNF alone	0.016	2.69

The rs2149092 (C-non-risk allele/T-risk allele) risk SNP abolishes IRF4/PU.1/ELF-1 binding site. IRF4 is an IBD susceptibility SNP that is lymphocyte specific and is essential for the differentiation of Th1, Th2, Th9, Th17 and T reg subsets. ELF-1 is a CD susceptibility SNP in the Japanese population. It is an ETS family transcription factor that is expressed in lymphoid cells, acts as both an enhancer and a repressor of expression and is involved in IL2 and IL23 signaling. PU.1 is also an ETS family transcription factor and is essential for early stages of T cell development. It down regulates γδ T Cells which are found in the mucosa and plays a role in innate immunity and when expressed in T _H9 cells, these cells drive T cell-mediated colitis via IL-9 receptor signaling in intestinal epithelial cells.
RNASET2 expression is decreased following TL1A treatment in IFN-γ secreting CD4⁺ T cells and that silencing of RNASET2 enhances TL1A mediated IFN-γ secretion. Clinical correlates have also been identified for RNASET2 disease associated SNPs, which include, but are not limited to therapeutic failure of thiopurine therapy, therapeutic failure of anti-TNF therapy, ANCA Sero-positivity, B2/B3 versus B1 (structuring/penetrating vs non-penetrating/non-stricturing) disease, an increase in length of intestinal resection, decreased time to second surgery and endoscopic recurrence of disease with high Rutgeerts score.
Various embodiments of the invention are described above in the Detailed Description. While these descriptions directly describe the above embodiments, it is understood that those skilled in the art may conceive modifications and/or variations to the specific embodiments shown and described herein. Any such modifications or variations that fall within the purview of this description are intended to be included therein as well. Unless specifically noted, it is the intention of the inventors that the words and phrases in the specification and claims be given the ordinary and accustomed meanings to those of ordinary skill in the applicable art(s).
The foregoing description of various embodiments of the invention known to the applicant at this time of filing the application has been presented and is intended for the purposes of illustration and description. The present description is not intended to be exhaustive nor limit the invention to the precise form disclosed and many modifications and variations are possible in the light of the above teachings. The embodiments described serve to explain the principles of the invention and its practical application and to enable others skilled in the art to utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed for carrying out the invention.
While particular embodiments of the present invention have been shown and described, it will be obvious to those skilled in the art that, based upon the teachings herein, changes and modifications may be made without departing from this invention and its broader aspects and, therefore, the appended claims are to encompass within their scope all such changes and modifications as are within the true spirit and scope of this invention. It will be understood by those within the art that, in general, terms used herein are generally intended as “open” terms (e.g., the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.).

Claims

1-34. (canceled)

35. A method of treating Inflammatory Bowel Disease (IBD) in a subject, the method comprising administering a therapeutically effective amount of a therapeutic agent to a subject, provided a single nucleotide polymorphism (SNP) at rs2149092 comprising a “T” at a nucleoposition 501 within SEQ ID NO: 2 is detected in a sample obtained from the subject.

36. The method of claim 35, provided a SNP at rs1819333 comprising an “A” allele at a nucleoposition 501 within SEQ ID NO: 1 is detected in the sample obtained from the subject.

37. The method of claim 36, wherein the IBD is severe IBD characterized by at least one of a therapeutic failure of an anti-Tumor Necrosis Factor alpha (TNFa) therapy, multiple flare-ups per year, stricturing disease, penetrating disease, and stricturing and penetrating disease.

38. The method of claim 36, provided a SNP at rs9355610 is detected in the sample obtained from the subject.

39. The method of claim 38, wherein the SNP at rs9355610 comprises a “G” allele at nucleoposition 501 within SEQ ID NO: 3.

40. The method of claim 36, provided a SNP at rs6478109 or a SNP at rs7848647, or a combination thereof, is detected in the sample obtained from the subject.

41. The method of claim 35, wherein the therapeutic agent comprises an anti-Tumor Necrosis Factor Ligand 1 (TL1A) therapy

42. The method of claim 35, wherein the therapeutic agent comprises a recombinant Ribonuclease T2 (RNASET2) polypeptide or protein.

43. The method of claim 35, wherein the IBD is Crohn's disease (CD), ulcerative colitis (UC), medically refractory UC (mrUC), or a combination thereof.

44. A method of diagnosing and treating inflammatory bowel disease in a subject, the method comprising:

a) subjecting a sample obtained from a subject to an assay adapted to determine a presence or an absence of a genotype comprising a single nucleotide polymorphism (SNP) rs2149092 comprising a “T” at a nucleoposition 501 within SEQ ID NO: 2;

b) detecting the presence or the absence of the genotype;

c) diagnosing inflammatory bowel disease (IBD) in the subject, provided the presence of the genotype is detected in step (b); and

d) treating the IBD in the subject, provided the subject is diagnosed with the IBD in (c)

45. The method of claim 44, wherein the genotype further comprises a SNP at rs1819333 comprising an “A” allele at a nucleoposition 501 within SEQ ID NO: 1.

46. The method of claim 44, wherein the IBD is severe IBD characterized by at least one of a therapeutic failure of an anti-Tumor Necrosis Factor alpha (TNFa) therapy, multiple flare-ups per year, stricturing disease, penetrating disease, and stricturing and penetrating disease.

47. The method of claim 44, provided the genotype further comprises a SNP at rs9355610 comprising a “G” allele at nucleoposition 501 within SEQ ID NO: 3.

48. The method of claim 44, wherein the assay comprises a genotyping assay selected from the group consisting of quantitative polymerase chain reaction (qPCR), a single nucleotide polymorphism (SNP) array, and sequencing.

49. The method of claim 44, provided the genotype further comprises at least one of a SNP at rs6478109 and a SNP at rs7848647.

50. The method of claim 44, wherein treating the IBD in (d) comprises administering to the subject a therapeutically effective amount of a therapeutic agent.

51. The method of claim 50, wherein the therapeutic agent comprises an anti-Tumor Necrosis Factor Ligand 1 (TL1A) therapy.

52. The method of claim 50, wherein the therapeutic agent comprises a recombinant Ribonuclease T2 (RNASET2) polypeptide or protein.

53. The method of claim 44, wherein the IBD is Crohn's disease, ulcerative colitis (UC), medically refractory UC, or a combination thereof.

54. A kit comprising:

a. a first nucleic acid probe comprising a first label, the first nucleic acid probe capable of hybridizing to at least a portion of a nucleic acid sequence provided in SEQ ID NO: 1 between nucleobases 300-700, including an “A” allele at nucleoposition 501; and

b. a second nucleic acid probe comprising a second label, the second nucleic acid probe capable of hybridizing to at least a portion of a nucleic acid sequence provided in SEQ ID NO: 2 between nucleobases 300-700, including a “T” allele at nucleoposition 501.